Cuban Studies [43]

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Editor’s Note This is the first volume of Cuban Studies produced under a new editorial team based at Harvard University. The journal was dormant for several years, a transitional period during which it depended on guest editors and occasional submissions. That period of uncertainty is over, and we are pleased to report that Cuban Studies, now one of the longest-lasting academic journals dealing with Cuban topics published anywhere in the world, has entered a new period. We began by appointing a new editorial board, as memberships in the previous board had all expired or were about to expire. The new board seeks to reflect the richness and diversity of the field of Cuban studies in terms of disciplines, approaches, authorship, and the geographic dispersion of its production. Serious scholarship on Cuba is produced today well beyond Cuba and the United States, the traditional centers of knowledge production about the island. There are important centers in Canada, Mexico, Spain, and Great Britain. Several scholars of Cuba, including a growing number of Cuban scholars, are also working in various academic centers in Latin America, stretching the geographic reach of the field, and benefiting from exchanges and perspectives brewed in other intellectual traditions. The field is no longer the near-exclusive monopoly of white males, a welcomed change that our editorial board seeks to reflect as well. Nor are studies of Cuba mostly confined to traditional disciplines such as history, political science, economics and literature. They now encompass cultural studies, gender studies, art history and criticism, LGBT studies, ethnography, anthropology, musicology, racial and ethnic studies, environmental studies, and more. We build on a long and distinguished tradition of excellence, collaboration, and intellectual integrity. Even during the times when studies about Cuba, no matter the subject, were hopelessly politicized, Cuban Studies was always a rare space of academic integrity, respectful dialogue, and productive exchange. Even at a time when Cuban culture was produced through what Ambrosio Fornet has called “reciprocal negations,” the journal sought to publish empirically based, methodologically sound, serious academic research. Some of the first academic polemics involving scholars based in Cuba and the United States were published by the journal, with great respect for all involved. We honor these legacies and benefit from the wisdom of more than forty years of editorial existence by having the founding editor of Cuban Studies (Carmelo MesaLago) and the former rotating editors—Jorge Domínguez, Jorge Pérez López,

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x : Editor’s Note Louis A. Pérez Jr., and Enrico Mario Santí—as “honorary members” of our board. They have deep, unparalleled knowledge about the evolution of Cuban studies—both the journal and the field. Following a sensible initiative introduced by Louis A. Pérez Jr. during his editorial tenure, we asked two colleagues to serve as book review editors, one based in Cuba and one based in the United States. They need no introduction. Lillian Guerra is a renowned historian of twentieth-century Cuba and the Caribbean, author of several key texts about the history of the island. Reinaldo Funes Monzote is an expert in the field of environmental studies, the top environmental historian of Cuba. Through their efforts, we will be publishing reviews about books on Cuba published all over the world, but we are particularly committed to the inclusion of books published in Cuba and of reviewers based in the island. We ask our readers and collaborators to bring interesting books to our attention: tracking today’s global editorial production is no easy task. Finally, we are lucky to have Cary Aileen García Yero as managing editor of Cuban Studies. A scholar of Cuban culture, with training in history and music, García Yero oversees the peer-review process of manuscripts, participates in editorial decisions, and helps assemble the volumes. Thanks to the dedication of this editorial team, and of our multidisciplinary board, we have produced this issue in record time. In addition to papers in history, culture and politics, this volume contains a central dossier on demography. This dossier charts some of the important changes experienced by the Cuban population—a concept that of course includes those living abroad—and some of the challenges posed by those changes (such as aging, or the changing composition of the expatriate community). A paper in the dossier looks carefully at infant mortality figures and raises poignant questions concerning methodologies and results. We seek to publish similar dossiers in every issue, with a variety of important themes and disciplinary approaches. Proposals from colleagues working on Cuba all over the world are welcome.

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SERGIO DÍAZ-BRIQUETS

Major Problems, Few Solutions: Cuba’s Demographic Outlook A B S T R AC T In the next several decades, Cuba will face major demographic challenges. As a result of persistent low fertility and high emigration rates, the population is contracting and aging. The aging population trend, as suggested by recent population projections, is irreversible over the short to medium term, posing considerable social and economic dilemmas for the future. How to address the needs of the elderly population will be at the center of the economic policy debate. Many rich countries facing comparable challenges are considering or implementing various policy options—in line with their prevailing social welfare policies—to cope with the aging crisis. Cuba, while facing far more adverse economic circumstances, will have to choose among these policy options as it implements inevitable social welfare reforms.

RESUMEN En las próximas décadas, Cuba enfrentará grandes retos demográficos. Debido a la persistencia de la baja fecundidad y altas tasas de emigración, la población se está contrayendo a medida que gradualmente envejece. La tendencia al envejecimiento poblacional, como sugieren varias proyecciones de población recientes, es irreversible al corto y mediano plazo, lo que plantea futuros dilemas sociales y económicos. Cómo satisfacer las necesidades de la población envejecida será tema central dentro del debate sobre políticas económicas a seguir. Muchos países ricos enfrentando retos comparables están considerando o implementando varias opciones de política —en consonancia con su régimen de bienestar social— para enfrentar la crisis del envejecimiento. Cuba, aunque confronta circunstancias económicas mucho más adversas, tendrá que elegir de entre estas opciones a medida que implementa inevitables reformas a su sistema de bienestar social.

Recent population trends indicate that in the next several decades Cuba will face major demographic challenges. As a result of a sustained fertility decline since the late 1960s, the country’s population growth rate has become negative, and the total population started to contract around 2010. This contraction will accelerate in years to come, as Cuba’s fertility remains below the replacement level and as the potential number of mothers, because of low past fertility, continues to diminish. The population decline will be further accentuated by high

3

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4 : Sergio Díaz-Briquets Male

550 440 330 220 Population (in thousands)

110

Cuba - 2014 100+ 95 - 99 90 - 94 85 - 89 80 - 84 75 - 79 70 - 74 65 - 69 60 - 64 55 - 59 50 - 54 45 - 49 40 - 44 35 - 39 30 - 34 25 - 29 20 - 24 15 - 19 10 - 14 5-9 0-4 0 0 Age Group

Female

110

220 330 440 550 Population (in thousands)

FIGURE 1.1. Cuba’s Population Pyramid, 2014 Source: U.S Census Bureau, “International Database,” International Programs, http://www.census .gov/population/international/data/idb/region.php?N=Results&T=12&A=separate&RT=0&Y= 2014&R=-1&C=CU.

net emigration rates—currently at record levels—although this will be slightly moderated by continued but limited gains in life expectancy. The significance of these demographic developments is visible in the rapid aging of Cuba’s population, more particularly in the rapid growth of the dependent elderly population that in coming years will need to be supported by ever-smaller cohorts of working-age adults. The demographic scenario is made more complicated by the irregularity of Cuba’s population pyramid, as shown in figure 1.1. Indentations and protuberances at various age groups reflect past fluctuations in fertility. These oscillations are in turn associated with changes in student, worker, and potential mother cohorts as members of those cohorts age over time. Already embedded in the population pyramid, these oscillations in age cohorts will require considerable sequential accommodations in the provision of education, employment, and other social services as the relative size of consecutive cohorts change. Secondary school enrollments in some years, for example, may contract, only to increase again as a larger age cohort reaches that same educational level. Despite being aware of these demographic trends, until quite recently Cuban authorities largely failed to formulate policies to minimize their most adverse consequences. The case can be made that the authorities instead decided to prioritize the resolution of other pressing problems at the expense of aggravating

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a worrisome demographic outlook. A case in point is Havana’s adoption of explicit and implicit policies to further emigration. While over the short and medium term emigration brings benefits to the strapped Cuban economy (by reducing labor-market and housing pressures and capturing foreign exchange through remittances and return tourist visits), in the long term emigration will deepen the unfolding demographic crisis as the predominantly working-age migrants not only depart but also give birth and raise children abroad. Regarding fertility, the situation is just as muddled. As most other countries experiencing below-replacement fertility began to voice alarm about the long-term economic and social adjustments that such low fertility regimes will demand, policy makers in Havana remained largely oblivious to their consequences. As late as 2007, Cuba and Denmark were the only two countries with total fertility rates (TFRs)—defined by the United Nations (2013c, n.p.) as “the average number of children a hypothetical cohort of women would have at the end of their reproductive period if they were subject during their whole lives to the fertility rates of a given period and if they were not subject to mortality. It is expressed as children per woman”—below 1.4 children per woman to declare in the biennial UN World Population Policies assessment that “their fertility level was satisfactory and required no intervention” (Goldstein, Sobotka, and Jasilioniene 2009, 685). Only in 2011 did Cuba reverse its position (as did Denmark), stating that fertility was too low, and announce a policy to raise its level (United Nations 2013b). What the elements of Havana’s fertility promotion policy are remain a mystery; until now only obscure references to such an initiative have been made public (Oficina Nacional de Estadísticas [ONE] 2011a, 15; de Armas Padrino 2013). In the same UN report, Havana declared itself not concerned about its working-age population, although it did indicate that population aging was a “major concern.” The report noted that in the previous five years, Cuba had both raised the statutory retirement age and reformed its pension system. Severity of the Demographic Contraction Population projections are useful in assessing the potential short- to long-term consequences of current demographic trends. As the future is uncertain, their relevance as reliable predictors of forthcoming developments is limited. However, when comparing various future scenarios (variants) built on contrasting assumptions of fertility, mortality, and migration, they have a useful function in evaluating alternative outcomes. Given the uncertainty, though, the analytical validity of population projections diminishes the further that they are carried into the future. Population forecasts differ from population projections in that the former assume that predicted outcomes will approximate future developments. A temporal caveat similar to that for population projections apply: the further

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6 : Sergio Díaz-Briquets a population forecast reaches into the future, the more likely it will be in error. Because of their nature, population forecasts are mostly done for planning purposes and focus only on brief time periods (e.g., a few years in intercensal periods). The latest population projections of the United Nations (2013c), updated in 2012, together with a population forecast issued by the ONE’s (2011a) Centro de Estudios de Población y Desarrollo, offer an opportunity to assess Cuba’s demographic prospects in years to come. While the Centro de Estudios de Población y Desarrollo refers to its statistical exercise as a projection, in most respects it was intended to serve as a forecast.1 It provides only one variant (median) so that all government and academic entities can rely on a “uniform number” (ONE 2011a, 2) and truncates the last fifteen years of the projection (2035–50) because “the changing demographic dynamic” results for those years “may yield information of limited utility” (ONE 2011a, 8). Rather than depend on national fertility, mortality, and net migration assumptions for the projection—as the United Nations customarily does—the ONE relied on a cascading approach whereby provincial statistics were aggregated to generate national assumptions, a process facilitated by virtually universal death and birth registration and the availability of a population register to which citizens must report, among other information, residential changes (ONE 2011a, 7). Results of the projections and the assumptions of the ONE and the UN Population Division are presented in the tables that follow. Where appropriate, additional information is offered to clarify concepts or elaborate on the projections’ implications. Mortality and Fertility Assumptions and Total Projected Population Table 1.1 presents five different population projections, together with related TFR assumptions for five-year periods. The table also includes the projected absolute number of births associated with each set of assumptions and the number of women of reproductive age yielded in each projection. Mortality assumptions do not require elaboration, as they are generally invariant across the five projections, starting at 79.2 years at birth for both sexes (females, 81; males, 77) in 2010–15 and gradually increasing to 82.4 (females, 84; males, 81) by 2030–35. Variability in TFR is significant, in particular regarding the spread between the United Nations’ low and high variants; by 2035–40, the latter is almost twice as high as the former. While initially the ONE and UN medium and constant variant TFRs are nearly identical, the ONE projection is far more optimistic than the UN medium variant projection regarding a future fertility upturn. A different perspective regarding what these rates imply for future population growth is provided by the number of births anticipated under each set of as-

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TABLE 1.1. Total Population Projections and Fertility Related Indicators, Cuba, 2010–2035 United Nations ONE Projected population (in thousands) 11,232 2010 a 2015 11,199 2020 11,124 2025 11,029 2030 10,905 2035 10,754 2050 — Fertility: TFRs 2010–2015a 1.52 2015–2020 1.56 2020–2025 1.59 2025–2030 1.62 2030–2035 1.64 2035–2040 1.66 2050–2055 — Births per year (in thousands) 2010–2015a — 2015–2020 — 2020–2025 — 2025–2030 — 2030–2035 — 2035–2040 — 2050–2055 — Women 15–49 (in thousands) 2010 a 2,941 2015 2,752 2020 2,496 2025 2,256 2030 2,176 2035 2,114 2050 —

Low

Medium

High

Constant

11,282 11,156 10,929 10,623 10,299 9,899 8,186

11,282 11,249 11,162 11,019 10,847 10,579 9,392

11,282 11,341 11,395 11,416 11,399 11,311 10,770

11,282 11,266 11,195 11,055 10,875 10,609 9,329

1.20 1.05 0.99 1.03 1.07 1.10 1.19

1.45 1.45 1.49 1.53 1.57 1.60 1.69

1.70 1.85 1.99 2.03 2.07 2.10 2.19

1.50 1.50 1.50 1.50 1.50 1.50 1.50

89 74 65 61 54 46 29

108 103 98 91 84 78 66

127 131 131 122 117 116 119

111 106 99 90 81 74 58

2,988 2,758 2,503 2,236 2,078 1,889 1,180

2,988 2,758 2,503 2,236 2,122 2,002 1,518

2,988 2,758 2,503 2,236 2,167 2,115 1,864

2,988 2,758 2,503 2,236 2,131 2,018 1,524

The starting year for the ONE projection is 2011. Source: ONE 2011a; United Nations 2013b (esa.un.org.wpp/unpp).

a

sumptions (ONE estimates are not available). The number is almost 2.5 times higher with the UN high variant as opposed to the low one, falling somewhere in between the medium and constant variants. The difference is more marked if the projections are carried fifteen more years into the future, as shown for the UN projections in the last row of the third panel of table 1.1. By 2050–55, the number of births projected by the UN high variant exceeds those under the low

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8 : Sergio Díaz-Briquets variant by a factor of four. The implications for future population growth are evident. That uncertainty surrounds the future behavior of the Cuban TFR and the number of live births is validated by recent past trends, as shown in table 1.2. The TFR fell from 1.63 in 2003 to 1.39 in 2006, only to rise above the 2003 level again after 2009. In terms of live births, the pattern deviates from that observed with the TFR, as the variability is more pronounced, with the live births being 8 percent fewer in 2012 than in 2003 even though TFR remained about the same. What accounts for these divergent trends can be found in figure 1.1, which depicts marked indentations in five-year age-group female cohort size, itself the result of past fertility fluctuations. The significance of these changes in cohort size is that even though Cuban age-specific fertility rates vary substantially as women age, at the various age groups they have been rather invariant over time. They are much higher at age 20–24 and 25–29 than at younger or older age groups.2 In the early 2010s, the largest age cohorts were procreating at their peak fertility rates. Over the next two decades, as aging proceeds, the relative size of women of reproductive age (age 15–49) will decline by close to 30 percent (see table 1.1), with the number of women age 20–24 and 25–29 declining even more (almost by half). So even if fertility rates remain constant, there will be fewer births. The ONE statisticians correctly anticipated Cuba’s actual fertility behavior between 2010 and 2012, the years immediately following the initial projection year. Rising fertility rates were assumed on the basis of the observed increase in TFR (and in total number of births) between 2006 and 2009 (see table 1.2). Whether or not projected TFRs materialize in years to come remains to be seen. A 2009 fertility survey revealed that whereas at all ages women desired

TABLE 1.2. Annual Total Fertility Rates and Number of Live Births: Cuba, 2003–2012 Year

TFR

Live Births

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

1.63 1.54 1.49 1.39 1.43 1.59 1.70 1.69 1.77 1.69

136,795 127,192 120,716 111,323 112,472 122,569 130,036 127,746 133,067 125,674

Source: ONE 2013, tables II.4 and II.1.

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more children (up to a completed family size of two children), most had not reached that target (ONE 2010, 68). Even if they do reach that target family size, as noted, fewer births should be anticipated given the much smaller cohorts of women entering childbearing age in the coming decades. Under the United Nations’ less favorable low and medium variant projections, the decline in births would be even more substantial, as shown in table 1.1. Projected Population Growth Rates and Net Migration Assumptions All projections agree that in decades to come Cuba’s population will contract in size and at an accelerating pace. The only difference is with regard to the rate of decline, as depicted in the upper panel of table 1.3. Particularly severe will

TABLE 1.3. Population Projection Growth Rates and International Migration Related Indicators: Cuba, 2010−2035 United Nations ONE Population growth rates (%) −0.07 2010−2015a 2015−2020 −0.13 2020−2025 −0.17 2025−2030 −0.22 2030−2035 −0.28 2035−2040 — Net migration ratesb (%) 2010−2015a — 2015−2020 — 2020−2025 — 2025−2030 — 2030−2035 — 2035−2040 — Annual net migrationb (thousands) 2010−2015a −35 2015−2020 −35 2020−2025 −26 2025−2030 −17 2030−2035 −9 2035−2040 —

Low

Medium

High

Constant

−0.22 −0.41 −0.57 −0.62 −0.79 −1.01

−0.06 −0.16 −0.26 −0.32 −0.47 −0.63

0.11 0.09 0.04 −0.03 −0.15 −0.25

−0.03 −0.13 −0.25 −0.33 −0.50 −0.67

−2.5 −2.5 −2.6 −1.9 −2.0 −2.1

−2.5 −2.5 −2.5 −1.8 −1.9 −1.9

−2.5 −2.5 −2.5 −1.8 −1.8 −1.8

−2.5 −2.5 −2.5 −1.8 −1.9 −1.9

−28 −28 −28 −20 −20 −20

−28 −28 −28 −20 −20 −20

−28 −28 −28 −20 −20 −20

−28 −28 −28 −28 −20 −20

The starting year for the ONE projection is 2011. ONE assumed that for the 2010−2015 and 2015−2020 quinquenniums, annual net migration would remain at the current average level gradually declining by 25 percent for subsequent fiveyear periods. Source: ONE 2011a; United Nations 2013b (esa.un.org.wpp/unpp). a

b

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10 : Sergio Díaz-Briquets be the population contraction under the UN medium and low variants, with the ONE projection suggesting a lower rate of decline. As noted previously, in Cuba’s case the demographic picture is more complicated, as low fertility is not the sole driver of population decline. Since the mid-1990s net migration (defined by the United Nations [2013c, n.p.] as the “net number of migrants, that is, the number of immigrants minus the number of emigrants[,] expressed in thousands”) has played an important role.3 And with regard to this variable, the ONE projection assumptions were well off the mark. Across its four variants, the United Nations used identical assumptions for net migration rate, minor fluctuations being dependent on age structure changes (see table 1.3). The 2010–15 assumptions are lower than the actual rates, as almost continuously since 1994 annual net migration has averaged about three per thousand. Furthermore, the United Nations projects declining net migration rates, a questionable assumption since the current high emigration rates will generate even higher likely future migration flows as today’s migrants acquire foreign citizenship and start claiming close relatives. While more realistic in its assumptions, the ONE also underestimated net migration during the years immediately following 2009. While ONE projected a net emigration of 35,000 annually between 2011 and 2015, statistics for 2011 and 2012 indicate that the reality considerably surpassed this estimate: the actual figures were 39,263 in 2011 and 46,662 in 2012 (ONE 2013, table VI.2). Further confounding ONE’s forecast validity was the longer-term net migration assumption. ONE assumed that the annual net migration level of 35,000 would remain unchanged for a decade, and then would start declining by 25 percent each subsequent five-year period until reaching zero by 2035–40 (ONE 2011a, 8). This is unlikely for reasons noted earlier, unless the nature of the Cuban polity and economy changes radically. Cuba’s Changing Dependency Ratios and Age Structure The economic and social implications of these demographic trends can be described as alarming and worsening. Tables 1.4 and 1.5 summarize the most commonly used dependency ratios and age structure components as generated by the ONE and UN projections. All projections anticipate an increase in the total dependency ratio (the population younger than age 15 plus the population age 60 and older) of close to 50 percent by 2035, or just about two decades into the future. Main discrepancies follow from differential fertility assumptions, the UN high variant yielding a higher ratio, as shown in the middle panel of table 1.4. A striking pattern is that regardless of UN variant, by 2050 (see table 1.4), the Cuban total dependency ratio will double regardless of fertility assumption. A similar outcome is expected concerning the old-age dependency ratio

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TABLE 1.4. Population Projections Dependency Ratio Indicators, Cuba, 2010–2035 United Nations ONE

Low

Medium

High

Constant

43 43 45 48 56 66 —

42 41 41 42 51 64 86

42 42 44 47 57 69 84

42 43 47 52 63 74 85

42 41 41 42 51 64 82

24 23 22 22 22 23 —

25 21 17 14 14 14 12

25 22 20 20 20 21 21

25 23 23 25 27 28 30

25 21 17 14 14 14 19

18 20 23 26 34 43 —

18 20 24 27 37 50 73

18 20 24 27 37 48 63

18 20 24 27 36 46 55

18 20 24 27 37 50 63

Dependency ratios Total 2010 a 2015 2020 2025 2030 2035 2050 Child 2010 a 2015 2020 2025 2030 2035 2050 Old age 2010 a 2015 2020 2025 2030 2035 2050

The starting year for the ONE projection is 2011. Source: ONE 2011a; United Nations 2013b (esa.un.org.wpp/unpp).

a

(population age 60 and older). Regardless of projection assumption, the ratio will more than double in the coming two decades, continuing to grow well into the future (see table 1.4). The old-age dependency burden is even more daunting when the size of the population age 80 and older is considered (see table 1.5): in unison with the old-age dependency ratio (this time defined as the population older than age 65, a more appropriate cutoff given Cuba’s high life expectancy and current statutory male retirement age), it will also double between 2010 and 2035. By 2050, more than 1.3 million Cubans will be 80+ years of age. However, the size of the population age 80 and older will begin to decrease at about this time, as the baby boom generation dies out. Still, the proportional weight of this age group in the age distribution will

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TABLE 1.5. Population Projections Age Structure Indicators (in thousands), Cuba, 2010–2035 United Nations ONE

Low

Medium

High

Constant

7,865 7,816 7,674 7,454 6,977 6,487 —

7,925 7,921 7,763 7,487 6,804 6,048 4,409

7,925 7,921 7,763 7,487 6,896 6,280 5,104

7,925 7,921 7,763 7,487 6,988 6,512 5,816

7,925 7,921 7,763 7,487 9,913 6,313 5,116

1,918 1,787 1,667 1,613 1,552 1,491 —

1,953 1,659 1,339 1,081 947 852 550

1,953 1,751 1,572 1,478 1,403 1,317 1,061

1,953 1,844 1,805 1,874 1,862 1,799 1,727

1,953 1,769 1,605 1,514 1,413 1,296 986

1,449 1,596 1,783 1,962 2,376 2,776 —

1,403 1,576 1,826 2,054 2,549 3,000 3,227

1,403 1,576 1,826 2,054 2,549 3,000 3,227

1,403 1,576 1,826 2,054 2,549 3,000 3,227

1,403 1,576 1,826 2,054 2,549 3,000 3,227

344 365 428 513 602 685 —

325 376 454 535 617 747 1,365

325 376 454 535 617 747 1,365

325 376 454 535 617 747 1,365

325 376 454 535 617 747 1,365

Age Group 15–64 2010 a 2015 2020 2025 2030 2035 2050 0–14 2010 a 2015 2020 2025 2030 2035 2050 65+ 2010 a 2015 2020 2025 2030 2035 2050 80+ 2010 a 2015 2020 2025 2030 2035 2050

The starting year for the ONE projection is 2011. Source: ONE 2011a; United Nations 2013b (esa.un.org.wpp/unpp).

a

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continue to be considerable. The significance of this trend is that the “old-old” population can be accurately forecast, and as is well known, the old-old consume a disproportionate share of health resources as they approach the end of life.4 Providing for their care will exact a heavy financial burden on the Cuban economy, just as the relative number of working-age adults declines from 18 to 24 percent (see table 1.5). Ameliorating the Current Demographic Trajectory Cuba’s low fertility rate and its implications are by no means unique. Most countries in Western Europe and its periphery are contending with similar, or even more daunting, prospects, as are a growing number of Asian nations (e.g., China, Singapore, Korea). Options to minimize the negative consequences of declining and aging populations include policies both to incentivize women and families to have more children and to attract foreign immigrants. An ongoing academic and policy debate behind the consideration of these options centers on the proposition that as societies complete their demographic transition to low death and birth rates, conditions arise that tend to favor the perpetuation of below-replacement fertility. Lesthaege (2010), a leading advocate of this view, argues that a second demographic transition may be unfolding, as in the mostly wealthier countries where it is manifested, the longing to have or not have children is motivated by the desire of women and families to satisfy higher-order aspirations, as formulated by Maslow (1954). This is far from the case in Cuba, where low fertility is more likely a concomitant of the combined effects of frustrated material expectations in a severely battered economy, where families struggle to satisfy basic needs; women are fairly well educated and have high rates of participation in the labor force; and contraception is widely available, with abortion in particular, being freely accessible on demand.5 Policies designed to increase birth rates are increasingly the focus of attention. While there is greater hope today than in the past about their potential, there is broad agreement—on the basis of European and Asian experiences— that “pronatalist policies, either explicit or implicit, have been effective,” but achieving success is expensive, as most social policy is (McDonald 2006, 487). This caveat suggests that the pronatalist policies hinted at but not yet formally articulated by Havana are unlikely to meet with success, as experiments continue with reforms of limited scope to reenergize the economy (Mesa-Lago and Pérez-López 2013). In fact, an overarching reform component centers on the reduction or elimination of financial subsidies, a goal contrary to that pursued by pronatalist policies, in which such incentives account for much of their success. Cuba could always target financial incentives to prospective mothers to encourage them to have children (to succeed, as shown by experiences

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14 : Sergio Díaz-Briquets elsewhere, the incentives must be significant), but in doing so, it would have to balance trade-offs among competing social demands in a challenged economic environment. Catch-up fertility does not appear to be in the cards for Cuba, as it might be a short-term option in Europe, since Cuban women—as opposed to European women—have not postponed childbearing (Lutz and Skirbekk 2005). The remaining option is to institute policies to alter international migration trends. On this score, however, Havana has embarked on a course that mortgages the future for immediate short-term economic gain.6 While most countries facing low fertility have few emigrants and generally encourage immigration, Cuba, as pointed out in the introduction, is following the opposite course. It does so by explicitly continuing to abide by the 1994 US-Cuba Migration Accord, which ensures the country a minimum of 20,000 US immigrant visas annually, a privilege not accorded by the United States to any other nation. And implicitly by having reformed in 2012 long-standing restrictive exit regulations (Ministerio de Justicia 2012), Havana knows full well it will result in more emigration and vociferously condemns the 1966 Cuban Adjustment Act and the “wet foot, dry foot” policy, US practices upon which Havana’s pro-emigration stance ultimately stands.7 While the migratory regulatory reform is a welcome development given its consistency with international norms of freedom of movement, it will lead to the permanent settlement of more Cuban nationals abroad.8 Rather than regarding this outcome as an unintended consequence of the exit policy reform, it should be viewed as the fulfillment of two explicit policy goals: minimizing internal discontent by exporting the disaffected and encouraging remittance flows. If there is an unintended consequence, it is that continued emigration will only worsen Cuba’s grave demographic future. Economic and Social Options to Cope with Population Aging How Cuba will respond to a shrinking and aging population in years to come is a big question. Few, if any, other nations facing Cuba’s current dire economic prospects—a limping, heavily indebted economy with low productivity and high unemployment—have ever confronted such a demographic scenario. European and Asian countries with comparable demographic profiles are generally wealthy and, more often than not, attract migrants, rather than experiencing something similar to Cuba’s emigration hemorrhage. The question is of more than rhetorical interest given the current debate about economic reforms as the historical leadership, in power for five decades, comes to terms with reality and looks for ways to generate growth. While the outcome of the economic reforms is uncertain, there is broad consensus regarding the desirability

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of maintaining (or recovering) the social safety-net features of the 1970s and 1980s (e.g., universal access to health care and pensions), crafted while the country was heavily subsidized by the Soviet Union. Assuming the economy were to recover, a reformed welfare regime would have to be designed to fulfill the economic, social, and health necessities of its aging population, including a sustainable pension system capable of satisfying basic needs. What the features of such a regime will be depends on the nature and extent of economic reforms, including responsibilities assigned to the state, the market (even if euphemistically called by another name, such as “nonstate sector”), and family as stewards of social risks and social security. According to these criteria, Aysan and Beaujot (2009, 709) identify four such regimes among Organisation of Economic Co-operation and Development (OECD) countries: The Liberal [in countries like the United States, Canada, United Kingdom] welfare regime . . . distinguished by the dominant role of the market in the management of social risks with lower responsibility on the part of the state and the family. In the welfare states of the Social Democratic [Denmark, Finland, Sweden] regime, the state plays a larger role than the market and the family in meeting the social needs of citizens. While all of these actors play a moderate role in the management of social risks in the Continental European [Austria, France, Germany] group, the family remains the key actor in the Southern European [Greece, Italy, Spain] group.

Within each of these regimes, safety net and pension reforms could be achieved by emphasizing or combining one of three approaches. These are: • cost containment • recalibration, or welfare reform through the removal of inefficient regulations • recommodification, or the effort to reverse dependency on the state through tightening eligibility or cutting benefits by dismantling some aspects of the welfare state

OECD countries have realized there is not a unique policy approach. The reform emphasis tends to vary from regime to regime. Social democratic and continental regimes, for example, place more attention on cost containment, whereas recalibration is a priority among southern European regimes, and recommodification the focus of liberal regimes. Allowing for significant differences in orientation, most OECD countries when dealing with pension reform, for example, have implemented policies “to delay retirement, to convert pensions to defined-contribution plans, and to have a higher dependence on private plans, all in the interest of seeking to achieve sustainability” (Aysan and Beaujot 2009, 718).

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16 : Sergio Díaz-Briquets Undoubtedly, the situation in Cuba is vastly different from that of OECD countries, but the lessons those countries have learned are nevertheless relevant. A major issue politicians must confront—at the center of the OECD reform debate, but apparently largely absent in the Cuba policy dialogue—is intergenerational justice. Future working-age cohorts will have to assume the burden of supporting older cohorts whose legacy—and that of more than five decades of revolutionary governance—is a bankrupt state. Cuba has no accumulated savings with which to pay for current or future safety-net costs in a context in which 60 percent of the elderly claim that pensions are insufficient to cover living expenses (ONE 2011b, 29). Under Cuba’s actual economic model, the defined-contribution and private retirement plan options are nonapplicable, whereas retirement ages have already been increased and other measures introduced to contain retirement and other social safety-net costs (Mesa-Lago and Pérez-López 2013, 156). While Havana’s ideological preference may be to move toward a welfare model akin to that of social democratic OECD countries, it simply does not have the financial means to finance or sustain such a system. Cuba is being forced de facto to accept a model that borrows much from the culturally familiar southern European system, in which the family, whether through the provision of day-today assistance or the provision of remittances, assumes the primary caregiving role. On top of that, many pensioners are being forced to supplement their pensions by joining the ranks of the self-employed. In essence, Havana is, if in a limited way, further recalibrating a deteriorated social safety net as it “recommodifies” the provision of services by formally reducing already much-diminished entitlements. The impact of such adjustments will be increasingly felt—as made evident during the September 2013 Council of Ministers meeting. There it was announced that while the state is prepared to assume a greater role in elderly care (by expanding the national network of assisted living facilities and nursing homes), blanket subsidies will be reduced or eliminated. The elderly who are better-off, including those with relatives who have the financial wherewithal, will be expected to defray some of the costs (Puig Meneses and Martínez Hernández 2013). The government has also announced that permits will be issued for nonstate actors to operate elderly care facilities. While these and other measures may relieve some financial pressures, they will not be enough: Cuba’s precarious economic and demographic situation demands far more radical and perhaps unreachable (from a demographic perspective) solutions. The burden could be not as severe if, in the future, Cuba were to embark, under a different economic model, on an economic growth path capable of unleashing the productive potential of its relatively skilled workforce. But regardless of the policy package and resources available for its implementation,

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the financial burden of providing for the elderly will be borne by the children of those generations who spent their lives under the rule of the Castro brothers. NOTES 1. In fact, the document’s presentation uses the term forecast (pronóstico) a few times. 2. In 2012, for example, the age-specific fertility schedule was as follows: for women age 15–19, 53.5 births per 1,000; age 20–24, 105.1; age 25–29, 94.2; age 30–34, 56.4; age 35–39, 23.2; age 40–44, 5.1; and age 45–49, 0.3 (ONE 2013, table II:4). 3. Emigration as a driver of negative population growth is significant in Cuba’s low-fertility environment. Its importance can be illustrated with official ONE data from 2012, when, despite the natural increase being positive, Cuba’s population contracted. A net migration of 46,662 individuals, together with 89,368 deaths, exceeded the 125,674 births recorded, thus resulting in a net population loss of 10,356 rather than a net gain of 36,306. 4. In the United States, on the basis of Medicare enrollment data, it has been estimated that “the oldest group (85+) consumes three times as much health care per person as those 65–74, and twice as much as those 75–84,” and other estimates suggest that “annual [health care] costs for the elderly are approximately four to five times those of people in their early teens” (Alemayehu and Warner 2004). 5. According to the United Nations, among reporting countries, Cuba had the second-highest abortion rate (28.9 per 1,000 women age 15–44) in the world, second only to Russia (37.4); Cuban women do not face any legal restrictions in securing abortions (United Nations 2013c). 6. In 2013 the Cuban authorities stated their satisfaction with the country’s emigration situation and stated that they expected it to remain unchanged, whereas in other countries facing similar demographic prospects, such as many former republics of the Soviet Union, there is concern about high emigration (United Nations 2013d). 7. Not known is whether the Cuban Adjustment Act will survive the US impetus for immigration reform. 8. Migration rates to the United States will likely continue to increase, thanks to the multiplier effect, as migrants become naturalized citizens and gain the privilege of petitioning for close relatives beyond the bounds of existing country quotas.

REFERENCES Alemayehu, Bernahu, and Kenneth E. Warner. 2004. “The Lifetime Distribution of Health Care Costs.” Health Services Research 39, no. 3 (June). http://www.ncbi.nlm.nih.gov/pmc/articles/ PMC13610281. de Armas Padrino, Iris. 2013. “Cuba Takes Steps to Increase Birth Rate.” Granma, June 27. Aysan, Mehmet F., and Roderic Beaujot. 2009. “Welfare Regimes for Aging Populations: No Single Path for Reform.” Population and Development Review 35, no. 4: 701–720. Goldstein, Joshua, Tomás Sobotka, and Aiva Jasilioniene. 2009. “The End of ‘Lowest-Low’ Fertility?” Population and Development Review 35, no. 4: 663–99. Lesthaege, Ron. 2010. “The Unfolding Story of the Second Demographic Transition.” Population and Development Review 36, no. 2: 211–51. Lutz, Wolfgang, and Vegrad Skirbekk. 2005. “Policies Addressing the Tempo Effect in LowFertility Countries.” Population and Development Review 31, no. 4: 699–720. Maslow, Abraham. 1954. Motivation and Personality. New York: Harper.

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18 : Sergio Díaz-Briquets McDonald, Peter. 2006. “Low Fertility and the State: The Efficacy of Policy.” Population and Development Review 32, no. 3: 485–510. Mesa-Lago, Carmelo, and Jorge Pérez-López. 2013. Cuba under Raúl Castro: Assessing the Reforms. Boulder, CO: Lynne Rienner Publishers. Ministerio de Justicia. 2012. “Decreto-Ley No. 302, Modificativo de la Ley 1312, ‘Ley de Migración’ de 20 de Septiembre de 1976.” Gaceta Oficial de la República de Cuba, October 16. ONE (Oficina Nacional de Estadísticas). 2010. Encuesta Nacional de Fecundidad 2009 . Havana: Centro de Estudios de Población y Desarrollo. ONE (Oficina Nacional de Estadísticas). 2011a. Proyecciones de la población cubana 2011–2035 . Havana: Centro de Estudios de Población y Desarrollo. ONE (Oficina Nacional de Estadísticas). 2011b. Resultados de la Encuesta Nacional de Envejecimiento Poblacional: Primer informe. Havana: Centro de Estudios de Población y Desarrollo. ONE (Oficina Nacional de Estadísticas). 2013. Anuario demográfico de Cuba 2012. Havana: Centro de Estudios de Población y Desarrollo. Puig Meneses, Yaima, and Leticia Martínez Hernández. 2013. “Continúa avanzando actualización del modelo económico cubano.” Granma, September 24. United Nations. 2013a. International Migration Policies 2013 Data Sheet. New York: Department of Economic and Social Affairs, Population Division. United Nations. 2013b. World Population Policies, 2011. New York: Department of Economic and Social Affairs, Population Division. United Nations. 2013c. World Population Prospects: The 2012 Revision. New York: Department of Economic and Social Affairs, Population Division. United Nations. 2013d. World Abortion Policies 2013 Data Sheet. New York: Department of Economic and Social Affairs, Population Division.

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RO B E RTO M . G O N Z A L E Z

Infant Mortality in Cuba: Myth and Reality A B S T R AC T Because of its low infant mortality rate (IMR), Cuba is often portrayed as a poor country that has reached social development levels of rich nations. In this article, however, I show that Cuba’s reported IMR seems very misleading. By exploring a sharp discrepancy between late fetal and early neonatal deaths, I develop a method for adjusting Cuba’s reported IMR. The results indicate that the adjusted IMR might be twice the reported one. Furthermore, Cuba’s adjusted IMR, although lower than those of Latin American and middle-income countries, is not at par with those of developed countries, as previously believed.

RESUMEN Debido a su baja tasa de mortalidad infantil (TMI), Cuba ha sido caracterizada como un país pobre que ha alcanzado niveles de desarrollo social muy similar al de naciones ricas. Sin embargo, este estudio muestra que la TMI reportada por Cuba no parece muy confiable. Luego de explorar una pronunciada discrepancia entre la mortalidad fetal tardía y la mortalidad neonatal precoz, este estudio propone un método para ajustar la TMI reportada por Cuba. Los resultados indican que la TMI ajustada puede ser el doble de la reportada. Además, la TMI ajustada, a pesar de ser menor que la de países latinoamericanos y de ingreso mediano, no es comparable a la de países desarrollados como se pensaba.

Introduction The development of health care and education is, undoubtedly, one of the most important goals of the Cuban revolutionary government. With respect to health care, lowering the infant mortality rate (IMR) has been perhaps one of the most coveted goals. The reasons behind the emphasis on this specific indicator are somehow clear: IMR is widely seen as a barometer for overall social development (at least two of the eight Millennium Development Goals are directly related to IMR); therefore, significant improvements in this indicator will certainly give legitimacy to the development agenda of the revolution. Such improvements have not gone unnoticed in general media and academia. In fact, Cuba is often cited as the epitome of the poor country that has

19

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20 : Roberto M. Gonzalez reached health standards comparable to those of rich nations.1 Not surprisingly, these claims seem to be very well founded on the reported statistics on IMR. For example, a quick look at figure 2.1 reveals that the IMR reported by Cuba is comparable to that of the United States, Canada, and Europe. In the year 2008 alone, for example, Cuba reported an IMR lower than that of the United States and Canada, and only slightly higher than the European average. Given such impressive performance along with a significant publicity effort by the Cuban government, the reputation of the infant care system has reached almost mythical proportions. In this article, however, I argue that such reputation might not be so mythical once the IMR reported by the Cuban government is analyzed with deeper scrutiny. A significant disparity between two important indicators directly related to IMR—namely, late fetal mortality rate

16

Cuba U.S. Canada Europe

IMR

12

8

4

0 1980

1985

1990

1995

2000

2005

2010

FIGURE 2.1. Trends in the Infant Mortality Rate (IMR) Notes: The infant mortality rate (IMR) refers to the number of deaths infants younger than one year old per 1,000 live births (i.e., [deaths younger than one year ÷ live births] × 1,000). The IMR for Europe is the average IMR for the following countries: Austria, Belgium, Bulgaria, Croatia, Czech Republic, Denmark, Spain, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Luxembourg, Netherlands, Norway, Portugal, Slovakia, Slovenia, Sweden, Switzerland, United Kingdom. Source: Anuario estadístico de salud, 2010 (Cuba); Statistics Canada; Canadian Vital Statistics, Birth, Death and Stillbirth Databases (Canada); Centers for Disease Control and Prevention and National Center for Health Statistics, National Vital Statistics System (United States); Eurostat (Europe); International Statistical Classification of Diseases and Related Health Problems, 10th rev. (ICD-10).

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(LFMR) and early neonatal mortality rate (ENMR)—suggests a substantial underreporting of infant deaths, which has led to artificially lower levels of IMR in Cuba. Using these two indicators, I develop a simple method for correcting the reported LFMR, ENMR, and IMR. Once the reported measures are adjusted, the corrected IMR might be as much as twice those reported. Furthermore, using the corrected measure suggests that, compared to countries with similar economic and social development, Cuba’s IMR is slightly superior. When compared to more developed nations, however, Cuba’s IMR is, by no means, at the same level. An overwhelming concern in comparative studies on infant mortality is the lack of comparable indicators on infant mortality, given that definitions of live births and infant deaths vary significantly by country. A key contribution of this article is that it uses a unique data set that allows for valid comparisons across countries (a feat that is unachievable with existing data sets).2 It is important to also highlight that previous treatments of this question, although very detailed and informative, relied heavily on personal accounts and anecdotal evidence. As a result, quantitative evidence of misreporting of the infant mortality rate by Cuban authorities is mostly missing in this literature. This article tries to fill this gap by presenting the first (at least to my knowledge) data-driven evidence of misreporting by Cuban health authorities. Last, in terms of methodology, this article proposes a relatively simple method for correcting the infant mortality rate that can be readily applied to any country in question. Data and Definitions Definitions Figure 2.2 presents a time series encompassing the gestational and infant periods along with the corresponding subperiods. The importance of this figure is that it helps illustrate the main components of fetal and infant mortality. It is important to highlight that the legal definitions for the different periods varies by country and even within countries (WHO 2006);3 therefore, I use here the definitions recommended by the World Health Organization’s (1993) International Statistical Classification of Diseases and Related Health Problems. Using figure 2.2, I stress four periods that are key for this study. First, the late fetal period begins at twenty-two completed weeks of gestation, at which time the weight of the fetus is normally 500 grams. Subsequently, the early neonatal period begins with the birth of the fetus and continues until seven days after birth is completed. Third, the perinatal period encompasses both the late fetal and the early neonatal period. Finally, the infant period is simply the period from birth to the completion of the first year of life. Notice that the early neonatal period is a component of the infant period while the late fetal is

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500 g (or 22 weeks)

Perinatal

Birth

7 th day

Early Neonatal

28th day

Post-neonatal

1 year

FIGURE 2.2. Components of the Gestational and Infant Periods Notes: Definitions provided by the International Statistical Classification of Diseases and Related Health Problems, 10th rev., vol. 2, instruction manual (Geneva: World Health Organization, 1993).

Conception

Late fetal

Neonatal

Infant

Infant Mortality in Cuba

: 23

not. Similarly the mortality rates are simply defined as the number of deaths occurring in one of the periods defined above per thousand live births.4 More specifically: Late Fetal Deaths ×1, 000 Total Births Early Neonatal Deaths ENMR = × 1, 000 Live Births Perinat al Deaths PMR= ×1, 000 Live Births Infant Deaths IMR= ×1, 000 Live Births LFMR=

(1) (2) (3) (4)

Notice, however, that as mentioned before, the definition of a live birth varies greatly from country to country and even within countries. For example, some countries declare a live birth only if the newborn weighs at least 500 grams or if the gestational age is at least twenty-two weeks, whereas other countries might have no lower limit on live birth classifications. This is, undoubtedly, a key obstacle for any comparative study since comparability across countries might be compromised by the different reporting criteria. To overcome this limitation, I use a unique data set on perinatal outcomes (both fetal and neonatal) collected by the EURO-PERISTAT (hereafter, PERISTAT) project, which allows me to create standardized measures for LFMR, ENMR, and IMR. The description of this data set is provided in the following section. Data Given the inherent difficulties in recording very early deaths, data sets on early neonatal and late fetal deaths are very scarce. A notable exception is a 2000 WHO study that compiled late fetal and early neonatal deaths for almost every country on the planet.5 The breadth of this data set, however, is tainted by one caveat: country-specific definitions for deaths and live births were used rather than standardized measures. This greatly limits comparability of the indicators, as definitions vary significantly by country. Fortunately, the PERISTAT project greatly overcomes this difficulty. The project was created in 1999 as part of the European Union’s Health Monitoring Programme to “monitor and evaluate maternal and child health in the perinatal period—pregnancy, childbirth, and postpartum—in Europe using valid and reliable indicators” (EURO-PERISTAT Project 2008). Data mainly originate from civil registrations, medical birth registers, hospital discharge data systems, perinatal surveys, and confidential inquiries and audits.6 Furthermore,

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24 : Roberto M. Gonzalez the collection process is overseen by representatives from each of the countries in the sample. The main advantage of this data set is, precisely, that fetal deaths are consistently recorded by birth weight (i.e., deaths of fetuses weighing less than 500 grams, 500–999 grams, 1,000–1,499 grams, and so on). This level of detail allows the creation of a standardized measure of fetal deaths across all PERISTAT countries and Cuba (i.e., all deaths of fetuses weighing 500 grams or more), a feat that was impossible using the WHO study. The report used in the WHO study provides information on late fetal and early neonatal deaths for twenty-six European countries for the year 2004. Data for the United Kingdom is divided into three regions: England and Wales, Northern Ireland, and Scotland. Therefore, the total sample amounts to twenty-eight observations. The estimation sample used in this article is reduced to twenty-five PERISTAT countries plus Cuba. The three exclusions in the PERISTAT sample are France, Greece, and Cyprus. France was excluded because of an obvious disparity in the reported live births and fetal deaths (only 14,737 live births are reported when, according to other sources, should be more 700,000). Cyprus and Greece were excluded for lack of data on fetal deaths.7 Finally, to allow for comparability, late fetal deaths are defined according to standard definitions (i.e., as all deaths of fetuses weighing 500 grams or more). The complete data set, including Cuba, is presented in table 2.1. Preliminary Evidence IMR and ENMR Country Comparisons Figure 2.3 depicts the reported IMR for Cuba and the countries in the PERISTAT sample for the year 2004.8 The average IMR was close to 5.02 infant deaths per 1,000 live births (represented by the solid horizontal line), with overall values ranging between 3 deaths per 1,000 live births in Sweden to slightly more than 9 in Latvia. From figure 2.3 it is clear that Cuba’s reported IMR is quite comparable to that of countries in the PERISTAT sample. With a reported value of 5.74 in 2004, Cuba’s IMR is slightly higher than that of the PERISTAT average but close to that of developed nations such as England and the Netherlands. Figure 2.4 shows that, not surprisingly, the trend in ENMR is very similar to that of IMR (recall from figure 2.2 that ENMR is a component of IMR, so this is somewhat expected). More important, it shows that with a reported ENMR of about 2.13 deaths per 1,000 live births, Cuba is not only below the sample average but also seems to outperform countries with solid economies such as Germany, England, and the Netherlands.

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Austria Belgium Czech R. Denmark Engl. & W. Spain Estonia Finland Germany Hungary Italy Latvia Lithuania Luxembourg Malta Netherlands N. Ireland Norway Poland Portugal Scotland Slovak Rep. Slovenia Sweden Cuba

AUT BEL CHK DEN ENGW ESP EST FIN GER HUN ITA LAT LIT LUX MAL NED NIR NOR POL POR SCO SLK SLO SWE CUB

78,934 76,872 97,671 64,521 639,721 505,638 13,990 57,569 646,626 95,137 539,066 20,355 29,480 5,469 3,887 181,006 22,362 57,111 356,697 109,356 52,911 52,388 17,846 100,158 127,192

Live Births 79,229 77,209 98,056 64,853 643,407 507,296 14,053 57,759 648,887 95,613 542,003 20,492 29,633 5,486 3,902 182,279 22,504 57,368 358,388 109,778 53,269 52,522 17,946 100,474 128,867

Total Births 295 309 325 200 3,201 1,416 63 152 2,257 461 2,189 133 152 16 15 1,001 106 236 1,734 380 315 132 98 303 1,675

LFD 133 157 130 193 1,685 467 47 113 1,446 322 1,077 77 96 9 12 544 59 83 1,272 183 117 113 38 160 271

END

299 736

320 303 366 286 3,157 2,002 88 195 2,918 628 2,134 191 240 19 23 891 90 172 2,414 426 261 365

ID 3.72 4.00 3.31 3.08 4.98 2.79 4.48 2.63 3.48 4.82 4.04 6.49 5.13 2.92 3.84 5.49 4.71 4.11 4.84 3.46 5.91 2.51 5.46 3.02 13.00

LFMR 1.68 2.04 1.33 2.99 2.63 0.92 3.36 1.96 2.24 3.38 2.00 3.78 3.26 1.65 3.09 3.01 2.64 1.45 3.57 1.67 2.21 2.16 2.13 1.60 2.13

ENMR

2.99 5.79

4.05 3.94 3.75 4.43 4.93 3.96 6.29 3.39 4.51 6.60 3.96 9.38 8.14 3.47 5.92 4.92 4.02 3.01 6.77 3.90 4.93 6.97

IMR 2.22 1.97 2.50 1.04 1.90 3.03 1.34 1.35 1.56 1.43 2.03 1.73 1.58 1.78 1.25 1.84 1.80 2.84 1.36 2.08 2.69 1.17 2.58 1.89 6.18

LFD/END ratio

Notes: LFD = late fetal deaths, END = early neonatal deaths, ID = infant deaths, LFMR = late fetal mortality rate, ENMR = early neonatal mortality rate, and IMR = infant mortality rate. The data for Belgium corresponds to the sum of figures for Brussels and Flanders. Sources: PERISTAT and the Anuario estadístico de salud (2010).

Country

Code

TABLE 2.1. PERISTAT Countries and Cuba

8

6

4

2

0

SWE NOR FIN LUX CHK POR BEL ITA ESP NIR AUT DEN GER NED SCO ENGW CUB MAL EST HUN POL SLK LIT LAT

Infant Mortality Rate (IMR)

10

FIGURE 2.3. Infant Mortality Rate (IMR) for PERISTAT Countries and Cuba, 2004 Notes: IMR calculated by the author using the reported infant deaths and live births in the PERISTAT study and the Anuario estadístico de salud (for Cuba) along with Equation 4. Country codes are provided in the appendix. Slovenia was excluded from the sample because of missing data on infant deaths. The horizontal reference line marks the sample’s average IMR of 5.02 infant deaths per 1,000 live births.

3

2

1

0

ESP CHK NOR SWE LUX POR AUT FIN ITA BEL SLO CUB SLK SCO GER ENGW NIR DEN NED MAL LIT EST HUN POL LAT

Early Neonatal Mortality Rate (ENMR)

4

FIGURE 2.4. Early Neonatal Mortality Rate (ENMR) for PERISTAT Countries and Cuba, 2004 Notes: ENMR calculated by the author using the reported early neonatal deaths in the PERISTAT study and the Anuario estadístico de salud (for Cuba), along with Equation 2. Country codes are provided in the appendix. The horizontal reference line refers to the sample’s average ENMR of 2.36 deaths per 1,000 live births.

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LFMR Country Comparisons This section presents a comparison of late fetal mortality rates (LFMR) across the PERISTAT countries and Cuba. To allow for comparability, deaths of all fetuses weighing 500 grams or more are used in the calculations for LFMR. Unlike ENMR, recall that LFMR is not a component of IMR. However, it is very clear from the medical literature and countrywide studies that both measures (LFMR and ENMR) are closely related. For example, the year 2000 WHO Neonatal and Perinatal Mortality: Country, Regional and Global Estimates study states that “Stillbirths [i.e., late fetal deaths] should equal, or more likely exceed, early neonatal deaths, as shown by data from developed countries, historical data sets and hospital data.”9 Such behavior is the result, the study argues, of neonatal and fetal deaths having many common causes and determinants. Further support for this claim is given in Velkoff and Miller’s (1995, 255) study of various Soviet republics, where they state that “deaths in the late fetal and early neonatal periods are believed to be caused by similar factors, including maternal illness and complications of pregnancy and delivery. Although the relative contributions of late fetal and early neonatal deaths might be expected to vary somewhat across time and location, we would expect the absolute level of the two components to be fairly consistent within a given republic.” For this reason, it is very well expected that countries with relatively low levels of ENMR should also have low levels of LFMR. Figure 2.5a presents LFMR and ENMR for PERISTAT countries, ranked by perinatal mortality rate. It is clear that the sample shows a pattern similar to that described by the WHO study and the medical literature. The levels of LFMR across the twenty-four European countries are relatively low and very compatible with the low levels of ENMR shown in figure 2.4.10 Not surprisingly, the correlation coefficient between early neonatal deaths (ENDs) and late fetal deaths (LFDs) is approximately 0.97. As suggested by the WHO study, LFMR tends to be slightly higher than ENMR; however, higher levels of ENMR are clearly associated with higher levels of LFMR, and vice versa. Given the basis of the WHO study and the results in the PERISTAT data set, the evidence seems unequivocal: ENMR should be similar in magnitude and closely related to LFMR. Evidence of Misreporting the ENMR and LFMR of Cuba Figure 2.5b adds the reported ENMR and LFMR for Cuba to figure 2.5a. It is obvious that the reported indicators for Cuba present a sharp contrast. Although Cuba equaled and even bettered the ENMR of many countries in the PERISTAT sample, the same does not seem to be true for LFMR. In fact, the LFMR level for Cuba is higher than that of all countries in PERISTAT, and also the difference is quite substantial. With a reported LFMR of nearly 13 deaths

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14

A. LFMR AND ENMR IN PERISTAT COUNTRIES

12 10 8 6 4 2 0 2

ESP LUX FIN SWE CHK SLK POR AUT NOR GER ITA BEL DEN MAL NIR SLO ENGW EST SCO HUN LIT POL NED LAT

4

B. LFMR AND ENMR IN PERISTAT COUNTRIES AND CUBA 14 12 10 8 6 4 2 0 2

ESP LUX FIN SWE CHK SLK POR AUT NOR GER ITA BEL DEN MAL NIR SLO ENGW EST SCO HUN LIT POL NED LAT CUB

4

FIGURE 2.5. LFMR and ENMR Notes: ENMR was calculated by the author as specified in figure 2.4. LFMR was calculated by the author using late fetal deaths reported by PERISTAT and the Anuario estadístico de Cuba. To allow for comparability between ENMR and LFMR, when calculating LFMR, live births were used in the denominator instead of total births, as specified by Equation (1). This was done to allow both measures to have the same denominator. The dashed lines emphasize the trend that ENMR and LFMR are positively correlated: higher (lower) levels of ENMR are associated with higher (lower) levels of LFMR.

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per 1,000 live births,11 Cuba’s LFMR is almost three times higher than the average LFMR of the PERISTAT countries and two times higher than that of Latvia, the country with the highest LFMR in the PERISTAT sample. This is quite unexpected given that countries with a high ENMR rank (i.e., low ENMR) should also display a high LFMR rank, as seems to be the case for PERISTAT countries. In fact, in their study of various Soviet republics Velkoff and Miller (1995, 255) argue that “comparing the rank of each republic for its early neonatal mortality with its rank for late fetal mortality gives us a way of assessing the extent to which early neonatal deaths may be misclassified as late fetal deaths in a given year.” To further clarify this point, figure 2.6 depicts the ratio of late fetal deaths to early neonatal deaths. Recall that from the arguments presented earlier, this ratio should be slightly higher than 1.12 For the PERISTAT countries this seems to hold as they exhibit an average ratio of about 1.84 (illustrated by the solid horizontal line in figure 2.6), with all observations ranging between 1.04 (Denmark) to slightly more than 3 (Spain). Cuba, however, exhibits a surprisingly high ratio of more than 6. In other words, LFDs appear to be six times higher than ENDs, when one should expect a much closer figure from solid evidence

6

Ratio of LFD to END

5 4 3 2 1

AUT BEL CHK CUB DEN ENGW ESP EST FIN GER HUN ITA LAT LIT LUX MAL NED NIR NOR POL POR SCO SLK SLO SWE

0

FIGURE 2.6. Ratio of Late Fetal Deaths to Early Neonatal Deaths Notes: Each dot represents the ratio of late fetal to early neonatal deaths for each country. The solid horizontal line represents the average ratio, excluding Cuba (i.e., average for PERISTAT countries).

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30 : Roberto M. Gonzalez from the medical literature and the PERISTAT sample. This is normally perceived in the demographics and literature as a sign of misreporting.13 The stark contrast between the ENMR and LFMR indicators in Cuba obviously raises the question of whether there is a problem of misreporting in either of the two measures. A possible explanation for such disparity might be that a coding error in the year 2004 (the year the PERISTAT is available and hence the year of study of this article) resulted in such high LFMR levels. However, the Anuario estadístico de salud reports a LFMR ranging between 10 and 15 deaths per 1,000 total births between the years 1987 and 2010. Moreover, the ratio of LFD to END has been consistently higher than 4 for the past fourteen years. A coding error is therefore very unlikely. Given this evidence, I argue that the figures for LFMR and ENMR are consistently misreported by Cuban authorities. Moreover, given similar instances of misreporting (see, e.g., Velkoff and Miller, 1995, on the case of the Soviet Union), I argue that late fetal deaths are overreported, whereas early neonatal deaths are underreported. Such misreporting may have two possible explanations. First, health professionals might be incorrectly classifying deaths that occur after birth (i.e., ENDs) as intrauterus deaths (i.e., LFD). This can result since “there may be misunderstanding of the definition of live birth and fetal death, or misunderstanding of the purpose of reporting” (WHO 2006, 8). This type of reporting error, however, is more typical in scenarios and countries where health professionals may not be properly trained or informed about the reporting rubrics. Second, authorities may purposely underreport ENDs to lower the IMR. The incentive for this type of misreporting lies in the technicality that the early neonatal deaths are counted in the infant mortality rate while late fetal deaths are not.14 This allows for the possibility that deaths that should be rightly classified as ENDs might, instead, be classified as LFDs so that the IMR remains relatively low. This could explain the inflated figures we observe in Cuba for LFD and the deflated figures we observe for END. An additional argument that may reinforce this claim as a source of misreporting is the fact that IMR is widely used in country comparisons and is a known measure of social development, whereas LFMR is barely known outside the health and policy circles. Hence, LFMR might be inflated (by deflating IMR) without much exposure. However, since the source of misreporting cannot be readily identified with the available data, I restrain from citing one reason as the main cause.

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Corrected Infant Mortality Rate Strategy for Estimating the Corrected ENMR and LFMR In this section I proceed by estimating the corrected ENMR and LFMR by making two key assumptions: (A1) The true LFD to END ratio for Cuba is within the range of the reported LFD to END ratio for the remaining PERISTAT countries. (A2) Perinatal deaths are correctly reported by Cuba.15 Assumption 1 is needed since the true ratio of late fetal to early neonatal deaths for Cuba is unknown. The assumption basically states that the true ratio of LFD to END in Cuba should be within 1.04 and 3.03, which are the minimum and maximum values of the LFD to END ratios observed in PERISTAT. The plausibility of this assumption comes from both the medical and the PERISTAT evidence cited earlier. Assumption 2 states that, although the END and LFD might be misreported, their sum (i.e., perinatal deaths) is not. The plausibility of A2 comes from the fact that perinatal deaths are relatively simpler to report (and hence less likely to be misreported), since, by definition, they do not depend on the classification of live births. More specifically, to classify a death as perinatal, the health professional is not required to determine or even know, based on standard classifications, whether the birth is live or not, which tends to be a significant source of confusion given the different definitions of a live birth.16 For example, a death occurring intrapartum might raise doubts as to whether it should be classified as a LFD or END. This death, however, can be classified as perinatal without any doubts. Therefore, although there might be some misreporting in the LFD and END, this might not be the case for perinatal deaths. From A1 I can specify the following two equations that will provide a lower and upper bound for Cuba’s true LFD to END ratio. Letting LFD* and END* denote true late fetal deaths and early neonatal deaths, respectively, a lower bound for the ratio in Cuba will be given by the following: LFD * = rmin END *

(5)

Similarly, an upper bound for the ratio will be given by: LFD * = rmax END *

(6)

where rmin and rmax are the minimum and maximum LFD to END ratio, respectively, for the PERISTAT countries. Both rmin and rmax are obviously observed in the sample.17

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32 : Roberto M. Gonzalez Following the definition of perinatal deaths and letting PD denote reported perinatal deaths, I can specify the following identity: PD = LFD* + END*

(7)

where PD is known and assumed to be correctly specified by A2. LFD* and END* are unknown parameters that need to be estimated. Equations (5) and (7) and equations (6) and (7) will each form a simple set of two equations in two unknowns (LFD* and END*), which would allow me to obtain estimates for the corrected late fetal and early neonatal deaths for each of the values for the lower and upper bounds of r. In their reduced form: END* =

1 PD 1 + rm

(8)

LFD* =

rm PD 1 +rm

(9)

for m = {min, max} Once lower and upper bounds are obtained from equations (8) and (9), one can easily calculate the late fetal and early neonatal mortality rates using the definitions in equations (1) and (2). Strategy for Estimating the Corrected IMR Once the range for the true late fetal and early neonatal deaths for Cuba is estimated, the results can be used to correct the reported infant mortality rate. Obviously, one would obtain a lower and upper limit for the true infant mortality rate from the lower and upper limit for the estimated early neonatal deaths. To do this, however, one further assumption is needed: (A3) The remaining components of infant deaths (i.e., late neonatal deaths and post-neonatal deaths) are reported correctly. A3 essentially states that all misreporting occurs at the early neonatal period and not after that. This, of course, is very unlikely given that misreporting may occur at other times. Therefore, the estimated infant mortality rate should be interpreted as a lower bound on the true infant mortality rate, as the true measure might be higher due to underreporting after the early neonatal period. Letting ID* and ID R denote true infant deaths and reported infant deaths respectively, and letting END R denote the reported early neonatal deaths, one can estimate a lower and upper bound for the corrected infant deaths in Cuba using: ID* =END *+( ID R − END R )

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(10)

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Infant Mortality in Cuba

: 33

where END* is estimated by equation (8). The term in parentheses represents all deaths occurring after the early neonatal period, which are assumed to be correctly specified by A3, while END* are the estimated bounds for the early neonatal deaths; therefore, their sum provides an estimate for the corrected infant deaths. Plugging equation (8) into (10) one obtains an expression for the true infant deaths that is a function of fully observable parameters: 1 ID* = PD+ ( IDR −ENDR ) 1 + rm

(12)

where ID R, END R, and PD are reported by Cuban authorities, and rm is the minimum and maximum ratios obtained from the PERISTAT sample. Therefore, equation (12) will give one estimate of the corrected infant deaths for each of the values of rm. Once ID* is obtained, calculating upper and lower bounds for the infant mortality rate is straightforward using equation (4). Results The estimated lower and upper bounds as well as a median value for late fetal, early neonatal and infant deaths are provided in table 2.2.18 For the sake of

TABLE 2.2. Reported and Estimated Late Fetal, Early Neonatal, and Infant Deaths and Mortality Rates for Cuba, 2004 Panel A. Total deaths Reported Late fetal deaths Early neonatal deaths Infant deaths

1,675 271 736

rmin

Estimated rmedian

rmax

990 955 1,420

1,261 685 1,150

1,463 483 948

Panel B. Mortality rates

Late fetal mortality rate Early neonatal mortality rate Infant mortality rate

Reported

rmin

Estimated rmedian

rmax

13.00 2.13 5.79

7.68 7.51 11.16

9.79 5.39 9.04

11.35 3.80 7.45

Notes: LFMR, ENMR, and IMR were calculated using Equations (1), (2), and (3), respectively, and the figure for live births and total births provided in the Anuario estadístico de salud (2010). The figures used were live births = 127,192 and total births = 128,867 for the year 2004. The values for the ratios are rmin = 1.04, rmedian = 1.80, rmax = 3.03, where is simply the median ratio observed in the PERISTAT data set.

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34 : Roberto M. Gonzalez comparison, table 2.2 also provides the figures reported by Cuban authorities. This estimation corrects for the observed inflation in late fetal deaths and deflation in early neonatal deaths. Special emphasis is given to the early neonatal deaths, as these form part of infant deaths and hence directly affect the infant mortality rate. There appears to be a high degree of underreporting of early neonatal deaths. In fact, the number of deaths during this period could actually be more than three times higher than the 271 deaths that authorities reported. This is similarly reflected in the actual number of infant deaths, which seem to be severely undercounted. In fact, close to half of all infant deaths seem to go unreported (1,420 versus 736) or, more likely, be misclassified as late fetal deaths. Panel B uses the estimated deaths presented in panel A to calculate mortality rates using equations (1), (2), and (4). Notice that for the year 2004, Cuban authorities reported an early neonatal mortality rate of only 2.13 deaths per 1,000 live births, which, according to the evidence provided earlier, sharply contrasts with the reported late fetal mortality rate of 13 deaths per 1,000 births. After correcting the reported rates, the early neonatal mortality rate might be more than three times higher than the reported rate (7.51 versus 2.13). The reported infant mortality rate is equally misleading. For instance, the infant mortality rate might possibly range between 7.45 and 11.16 infant deaths per 1,000 live births instead of the 5.79 reported by authorities. To put these figures in perspective, the actual rate might be as much as 92 percent higher (11.16 versus 5.79) than the reported one. An important takeaway from this analysis is that the adjusted figures for Cuba do not appear to be comparable to that of more developed countries, as it has been generally believed. In fact, mortality rates are considerably higher than those of PERISTAT countries. This is, precisely, the subject of the next section. Updated Ranks The fact that the IMR is a widely used indicator for cross-country comparisons makes the exercise of analyzing the effect of the corrected IMR on the relative rankings a necessary one. Figure 2.7 shows box plots of the infant mortality rates for high- and middle-income countries (panel A) and European, Latin American, and North American countries (panel B). Data used in this section as well as the income (high, middle) and geographical divisions come from statistics reported by the World Bank (2004). The solid and dashed lines represent the median and the lower and upper bounds for the estimated infant mortality rate in Cuba. First, notice in panel A that the widely held belief that Cuba’s infant mortality rate is at par with that of high-income countries seems to have no foundation once this indicator is corrected. Furthermore, it is clear that the estimated median value in Cuba is substantially higher than the median

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PANEL A. DIFFERENT INCOME LEVELS

High Income

Middle Income

0

10

20

30

40

50

60

Infant Mortality Rate, 2004 PANEL B. DIFFERENT REGIONS

Europe

Latin America

North America

0

20 40 Infant Mortality Rate, 2004

60

FIGURE 2.7. Corrected Ranks by Income Levels and World Region, 2004 Notes: Panels use World Bank definitions for geographical location as well as income division (e.g., high, middle). The solid vertical line represents the median IMR estimated for Cuba. The vertical dashed lines represent the minimum and maximum estimated IMR for Cuba. Source: World Bank Databank (http://data.worldbank.org).

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36 : Roberto M. Gonzalez for high-income countries (9.0 in Cuba versus 4.6 in high-income countries). At the same time, however, the estimated median for Cuba is lower than that of middle-income countries. From this evidence, it might be safe to conclude that Cuba’s true infant mortality rate, though superior to that of middle-income countries, is by no means at par with that of high-income countries. Panel B provides box plots for the infant mortality rates for different regions of the world. The choice of Europe and North America is to illustrate how Cuba’s true infant mortality rate fares compared to that of the relatively rich countries to which it is usually compared. The choice of Latin America comes from the fact that Cuba is often cited as a “positive” outlier, in the sense that it displays infant mortality indicators vastly superior to those of the region. Similar to the conclusions from panel A, Cuba’s estimated median rate is higher than that of Europe and North America. This, however, is quite expected given the results in panel A and the substantial overlap of Europe, North America, and high-income nations. Surprising, however, is the fact that compared to Latin America, Cuba might not be a “positive” outlier after all. Although still low compared to the region, the infant mortality rate in Cuba might be higher than that of Chile (8 deaths per 1,000 live births) and close to that of Costa Rica (9.4 deaths per 1,000 live births). Conclusion The findings in this study cast enormous doubts onto both the validity of the reported Cuban statistics and commonly held beliefs about the superior quality of public health in Cuba. Additionally, the findings show that the relative ranking of Cuba suffers greatly when underreporting is taken into account. A similar argument holds also for other key indicators such as late fetal and early neonatal mortality rates, which have relatively high figures that are both high on international standards and very discordant with the reported figures. For these reasons, I make two recommendations. First, statistics reported by the Cuban government should be more closely scrutinized. In other words, close attention should be given to other key determinants of social and early health development, such as fetal death rates, to ensure that these statistics are not suspiciously inflated, as seems to be the case in Cuba. Second, I suggest using an “augmented,” or more inclusive, measure of mortality that includes both infant and late fetal deaths, given the similarities between the determinants of these two types of mortality as well as the equal importance that both have as indicators of social and health development in a country. Additionally, such a measure might help reduce the incentive to misclassify the components of perinatal deaths in order to reduce the infant mortality rate.

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NOTES 1. I am thankful to Dr. Roberto Martín Gonzalez for sharing his vast knowledge on the Cuban system of reporting health statistics. I am also thankful for the many useful comments from participants at the Twenty-Third Conference of the Association for the Study of the Cuban Economy. Any remaining errors are mine. See, for example, the New York Times coverage of Michael Moore’s documentary Sicko, which mentions that “Statistics . . . show that the people of Cuba and the United States have about the same life expectancy . . . while infant mortality in Cuba is significantly lower than in the United States” (De Palma 2007). Recently, Spanish news agency EFE reported that Cuba announced the lowest infant mortality rate in its history, at around 4.2 deaths per 1,000 live births (Agencia EFE 2014). This is noticeably lower that than of the United States, for example, which reported a rate of 5.2 per 1,000 live births for that same year. For a treatment of this issue that is more academically oriented, see Cooper, Kenelly, and Orduñez-García (2006). 2. The data set is obtained from the EURO-PERISTAT project. 3. For an idea of how the definitions of live birth, late fetal, and early neonatal deaths vary across a sample of European countries, see McFarlane et al. (2003) or European Commission (2003). 4. It is important to note that the definition of late fetal mortality rate (LFMR) uses total births (live births + fetal deaths) as the denominator instead of only live births, as other definitions of mortality do. For this reason, LFMR and ENMR do not necessarily add up to the perinatal mortality rate. 5. The same study was later repeated in 2004. For countries for which no data was available because of missing or questionable recording, agency estimates were provided. 6. For more information on data collection for each country, see the EURO-PERISTAT Project (2008). 7. Although data on fetal deaths by gestational age was provided by Greece, data on fetal deaths by birth weight was missing. 8. The IMRs presented in figure 3 were calculated by the author using the reported infant deaths and live births in the PERISTAT study and the Anuario estadístico de salud (for the case of Cuba; Dirección Nacional de Registros Médicos y de Salud 2011) along with equation (4). 9. In a 2004 follow-up study by the WHO, the authors found that average LFMR and ENMR across various world regions are very close. For example, Africa had an LFMR of 28 and an ENMR of 29; Asia, LFMR of 25 and ENMR of 23; Europe, LFMR of 5 and ENMR of 4; Latin America and the Caribbean, LFMR of 8 and ENMR of 10; North America, LFMR of 3 and ENMR of 3. Such numbers certainly give validity to the argument that ENMR and LFMR are closely related in their magnitudes. The caveat, however (which the authors recognize), is that many of the countries in the study have varying definitions of live births and fetal deaths; therefore, the numbers provided by the authors, although illustrative, are not fully comparable across regions and countries. For this reason, I refrain from using that data set and instead take advantage of the comparability that PERISTAT allows. 10. For ease of comparison, the ENMR in figure 2.4 is also shown in figure 2.5 on the negative section of the vertical axis. 11. Contrary to the definition of LFMR given in equation (1), I use live births in the denominator instead of total births to keep comparability between the LFMR and the ENMR. I also do this for all countries in the PERISTAT sample. 12. Recall that the WHO study states that late fetal deaths should equal or more likely exceed early neonatal deaths. Therefore the ratio of LFD to END should be slightly higher than 1. 13. Velkoff and Miller (1995, 255), for example, state, “If early neonatal deaths are being

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38 : Roberto M. Gonzalez systematically misclassified as late fetal deaths, then the ratio of late fetal to early neonatal mortality will be high compared to its expected value.” 14. Recall from figure 2.2 that the early neonatal deaths are a component of the infant mortality rate, whereas late fetal deaths are note. 15. Recall from figure 2.2 that perinatal deaths are the sum of late fetal and early neonatal deaths. 16. Recall from figure 2.2 that, in this study, the definition of perinatal deaths used are all deaths that occur in the period in which fetuses weigh 500 grams or more and newborns are seven days old or less. The data on PERISTAT as well as the Anuario estadístico allows for making this distinction. 17. In this case, rmin = 1.04 and rmax = 3.03. 18. The median value is simply obtained using equations (5), (6), and (7) but using the median ratio in PERISTAT rather than the minimum and maximum values as specified in equations (5), (6), and (7).

REFERENCES Agencia EFE. 2014. “Cuba ends 2013 with lowest infant mortality rate in its history.” Global Post, January 2. http://www.globalpost.com/dispatch/news/agencia-efe/140102/cuba-ends-2013 -lowest-infant-mortality-rate-its-history. Cooper, Richard S., Joan F. Kenelly, and Pedro Orduñez-García. 2006. “Health in Cuba.” International Journal of Epidemiology 35 (4): 817–824. De Palma, Anthony. 2004. “‘Sicko,’ Castro and the ‘120 Years Club.’” New York Times, May 27. http://www.nytimes.com/2007/05/27/weekinreview/27depalma.html?_r=1&. Dirección Nacional de Registros Médicos y de Salud. 2011. Anuario estadístico de salud, 2010. Havana: Ministerio de Salud Pública. European Commission. 2003. Demographic Statistics: Definitions and Methods of Collection in 31 European Countries. Luxembourg: Office for Official Publications of the European Communities. European Commission Statistical Database (Eurostat). http://epp.eurostat.ec.europa.eu/portal/ page/portal/statistics/search_database. EURO-PERISTAT Project. 2008. European Perinatal Health Report. http://www.europeristat .com/reports/european-perinatal-health-report2004.html. McFarlane, A., M. Gissler, F. Bolumar, and S. Rasmussen. 2003. “The Availability of Perinatal Health Indicators in Europe.” European Journal of Obstetrics and Gynecology and Reproductive Biology 111: 15–32. Statistics Canada. Canadian Vital Statistics, Birth, Death and Stillbirth Databases. http://www23 . statcan.gc.ca/imdb/p2SV.pl?Function=getSurvey&SDDS=3234&Item_Id=1530 &lang=en. United Nations (n.d.). Millennium Development Goals. http://www.un.org/millenniumgoals/. Velkoff, Victoria A., and Jane E. Miller. 1995. “Trends and Differentials in Infant Mortality in the Soviet Union, 1970–90: How Much Is Due to Misreporting?” Population Studies 49 (2): 241–258. World Bank. World Databank. http://data.worldbank.org. World Health Organization. 1993. International Statistical Classification of Diseases and Related Health Problems, 10th rev. Geneva: World Health Organization. World Health Organization. 2006. Neonatal and Perinatal Mortality: Country, Regional and Global Estimates. Geneva: World Health Organization.

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World Health Organization. 2007. Neonatal and Perinatal Mortality: Country, Regional and Global Estimates 2004 . Geneva: World Health Organization. Xu, J. Q., K. D. Kochanek, S. L. Murphy, and B. Tejada-Vera. 2010. “Deaths: Final Data for 2007.” National Vital Statistics Reports 58 (19). Hyattsville, MD: National Center for Health Statistics.

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A L E JA N D RO P O RT E S AND AARON PUHRMANN

A Bifurcated Enclave: The Economic Evolution of the Cuban and Cuban American Population of Metropolitan Miami A B S T R AC T We summarize the history of the Cuban economic enclave of Miami, from its origins to the present. The uniqueness of the story lies not only in the emergence of this phenomenon and its early consequences but also in its bifurcation following the episode of the March boatlift of 1980. We examine the reasons for the split between the earlier waves of Cuban exiles arriving in the 1960s and 1970s and subsequent refugees. On the basis of census data, we are able to document the economic evolution of the Cuban and Cuban American population of the Miami metropolitan area, the significant divide in economic returns in favor of entrepreneurs, and the wide gap in personal and family incomes between pre-1980 Cubans and their children and those coming after that date. Reasons why Mariel and post-Mariel Cubans have done much more poorly both as entrepreneurs and as workers in the Miami labor market are examined. Implications for the educational attainment and social adaptation of their US-born children, the second generation, are documented on the basis of data from the Children of Immigrants Longitudinal Study (CILS).

RESUMEN El texto resume la historia del enclave económico cubano en Miami, desde sus orígenes hasta el presente. Lo particular de esta historia yace no solo en sus orígenes y consecuencias tempranas, sino en su bifurcación después del episodio del Mariel en marzo de 1980. Examinamos las razones de la ruptura entre los primeros grupos de exiliados cubanos que llegaron en los 1960–1970, y los refugiados que llegaron después. Basándonos en datos censales, hemos documentado la evolución económica de la población cubana y cubana-estadounidense del área metropolitana de Miami, la división significativa en ingresos a favor de los empresarios, y la diferencia en los ingresos personales y familiares entre cubanos llegados antes de 1980, sus hijos, y aquellos que llegaron después de esta fecha. También analizamos las razones por las cuales a los cubanos que llegaron cuando el Mariel y después les ha ido mucho peor como empresarios y trabajadores en el mercado de trabajo de Miami. La educación alcanzada y adaptación

40

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A Bifurcated Enclave : 41 social de sus hijos nacidos en los Estados Unidos, la segunda generación, son documentados basados en información obtenida del Children of Immigrants Longitudinal Study (CILS).

The successive phases of the Cuban exodus up to 1980 were traced numerous times in the specialized literature of that period.1 They came to an end with the Mariel exodus of that year, which marked a point of inflection in the development of the expatriate community and the economic enclave that it had managed to build. The Mariel episode and its consequences are also a wellknown story that has been told many times in the social science and popular literature.2 For our purposes here, Mariel produced two major consequences. First, it shifted the mode of incorporation of new Cuban arrivals in the United States from positive to negative. President Carter’s declaration that the United States would continue to receive all new Cuban escapees “with open arms” represented the last gasp of the previous policy of an unrestricted, benign US government stance. Realities on the ground proved too much, and the official attitude shifted toward denying the Mariel arrivals permanent settlement. Instead, a new, and more ominous legal category was invented for them— “entrants, status pending.”3 The image that Cubans had carved in American public opinion also suffered a marked deterioration. The exiles ceased to be a “model minority” and the “builders of the new Miami” to become just another third-world minority forcing its way onto American shores. In public opinion polls taken at the time, Cubans ranked among the least popular groups in the country.4 This abrupt change in their public image was one reason, albeit not the only one, the old exile community also shifted its stance—from welcoming the new arrivals to creating social distance from them. The derogatory term marielito made its appearance about that time.5 For displaced prerevolutionary elites whose sole source of comfort in exile had been their cozy relationship with Washington and the welcoming attitude of the American public, the stigma brought about by Mariel was intolerable. The successful anti-Spanish referendum held in Miami-Dade County in the same year as the Mariel episode was the last straw. These events marked the beginnings of the bifurcation of the Cuban expatriate population into two distinct communities, with significant consequences for the future. In 1980, and even after Mariel, Cubans in the United States represented an elite group with average levels of education, occupational status, and selfemployment comparable or superior to the US population and above that of other Latin immigrant groups. Their transformation into another third-world minority was not inevitable. It happened instead as a consequence of that momentous split. The successive phases of this transformation and its complex

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42 : Alejandro Portes and Aaron Puhrmann effects both for the Cuban American community and for its relations with the island are the story that we attempt to trace here. Reactive Mobilization and the Closure of the Enclave The reaction of the old Cuban upper and middle classes to the anti-bilingual referendum and the stigma of Mariel took two forms. First, a political shift from an exclusive concern to overthrowing the Castro regime toward domestic mobilization in self-defense; second, the closing of the networks of the enclave to the new arrivals.6 Following the events of 1980, Cuban exile businesspeople who had believed themselves integrated into the Anglo mainstream began to withdraw from its organizations and create parallel ethnic associations. Facts about Cuban Exiles (FACE) and the Cuban American National Foundation (CANF) were founded at that time. Plans were made to run candidates for local office. More important, a new discourse began to emerge portraying the exile community itself as the solution to Miami’s problems and the positive transformation of the city: Before the “Great Change,” Miami was a typical southern city, with an important population of retirees and veterans, whose only activity consisted in the exploitation of tourism during the sunny winters. No one thought of transforming Miami into what it is today. It is no exaggeration to say that the motor of this Great Change was the Cuban men and women who elected freedom and came to these shores to rebuild their homes and face with courage an uncertain future. . . . These last decades of the twentieth century have witnessed the foundation of a dynamic and multifaceted Miami over the past of a Miami that was merely provincial and tourist-oriented. Today, the level of progress has reached unanticipated heights, beyond the limits of anyone’s imagination.7

The Cuban “success story” in the United States is evident in statements such as these. What is often neglected is its reactive character. The anti-bilingual referendum and related measures were attempts by the Anglo elites and native population of South Florida to put Cubans “in their place.” Instead, old exiles reacted by mobilizing their considerable economic power and collective solidarity, putting them at the service of electoral politics.8 By the mid-1980s, the mayors of Miami, Hialeah, West Miami, and several smaller municipalities in Dade County were Cuban born, and there were ten Cuban Americans in the state legislature. The 1990s added three federal congressional representatives, and the 2000s, two federal senators from Florida, first Mel Martínez and then Marco Rubio. In areas of Latin concentration in South Florida, it became scarcely worthwhile to run for office if one was not Cuban American.9 The Miami congressional delegation registered several notable successes, primarily in the form of successive laws tightening the economic embargo

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A Bifurcated Enclave : 43 against Cuba, but also others benefiting the exile community. The Cuban Adjustment Act, passed in the context of the Cold War in 1966, granted Cuban refugees and their kin expedited access to US legal permanent residence outside quota limits and other qualifications. The waiting period for a permanent residence visa was shortened from two years to only one in 1976. The law kept in the books with the support of Cuban American officials, in combination with the immigration agreement between the US and Cuban governments in 1994, granted Cuban citizens arriving on US shores near-automatic asylum, followed by a fast-track process toward permanent residence and citizenship.10 A fundamental but commonly forgotten aspect of this story of political mobilization is that it involved the older exiles—those arriving in the 1960s and 1970s and eventually their children—but largely excluded Mariel entrants and subsequent arrivals. These later refugees, settling mainly in the workingclass city of Hialeah and impoverished sections of Miami, were not the beneficiaries of the networks of solidarity that had allowed earlier exiles to find jobs in Cuban enclave firms, move ahead, and eventually become entrepreneurs themselves. The “character loans” that had given earlier Cuban entrepreneurs access to start-up funds solely on the basis of their known character were unavailable to the new arrivals. Other forms of co-ethnic solidarity were also withdrawn. From the viewpoint of earlier and better-established exiles, Mariel and post-Mariel arrivals were different—raised under the revolution, they lacked the work ethic and the principled anticommunist political stance of their predecessors. They could not be trusted. In the words of a Cuban American social worker in 1983: The quality of Cuban refugees who arrived in the seventies is very different from those who came in 1980. About one-third of the 125,000 Marielitos are trash—delinquents, homosexuals. Their effects on Miami have been terrible. In our office, we try to find employment for them and provide them with transportation to their new jobs. However, many employers don’t want Mariel refugees. The reason why the Marielitos are different is that many came alone, rather than as part of family groups. Eighty percent of those who come here asking for jobs are lone individuals. . . . And they have high expectations: they don’t accept minimum wages. They say, “It’s too little,” and prefer to continue living on welfare and food stamps.11

The near-automatic granting of asylum, the Cuban Adjustment Act, and the closure of the enclave worked at cross-purposes: the first two facilitated a continuous stream of new refugees from the island; the third excluded them from the networks of co-ethnic solidarity that had been fundamental in the economic mobility of the pre-1980 exile community. Consequences of this contradiction started to appear in census statistics as early as 2000, pointing to major transformation in the character of the Cuban expatriate community.

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44 : Alejandro Portes and Aaron Puhrmann Cuba and the United States: A Pas de Deux across the Strait of Florida The Mariel exodus was seen as a catastrophe in Miami, but it was a political triumph for the Cuban government. In one fell swoop, it erased the negative image linked to the occupation of the Peruvian embassy in Havana, got rid of common prisoners and other undesirables, and stigmatized its opposition abroad. The use of the strategy of free departure has been used repeatedly by Cuban authorities as a temporary safety valve to reduce internal opposition.12 What changed with Mariel was the stance of the US government. While the Cuban Adjustment Act remained in force, thanks in part to the political power of the old exiles, new refugee flows from the island were neither promoted nor welcome. Thus, the positive context of reception that had greeted earlier exile arrivals disappeared. Post-1980 refugees had to fend for themselves, settling in poorer areas of Miami while maintaining ties with kin and friends on the island for emotional support. The shift in the US stance was made evident during the rafters’ crisis of 1994, during which escapees were not welcome on US shores but instead taken to the US base in Guantánamo and to a limbo of indefinite detention. The obvious intent was to discourage people from escaping the island. The governmental agreement that eventually ended the crisis created a program of orderly departures from the island not because of an official US desire for fresh refugees but as a way to prevent new catastrophic episodes at sea.13 Up to that point, Cuban authorities had seen these episodes as a way to get rid of their opponents and other undesirables, but by the mid-1990s, things started to change. The negative mode of incorporation of post-1980 refugees encouraged their continuing ties with those left behind on the island. They may not be popular with established exiles in Miami, but they were so with their acquaintances back home. These were the beneficiaries of a continuous flow of resources that, in the impoverished condition of the island, became decisive for survival. From their meager South Florida salaries, the new refugees managed to send back enough in money and kind to keep their families alive.14 Thus, a new phase of the Cuban-US saga was inaugurated with the return trips of the new refugees, a movement that gained momentum despite all attempts by the old-style exile leadership in Miami to set it back. Migration from Cuba became a two-way movement rather than a one-way escape from political oppression. At some point, it dawned on Cuban authorities that the escapees, rather than posing a threat, had become a valuable economic resource. Transnationalism: Rescinded, Reborn, Resurgent The close historical ties of Cuba and the United States were effectively eliminated with the advent of the revolution. Thereafter, only a few brave souls

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A Bifurcated Enclave : 45 dared to go back after having been granted asylum in the United States. It was, in the words of Cabrera Infante, a “world in black and white” where the frontal confrontation between the revolutionaries and the old Cuban upper and middle classes left little space for dialogue, much less for regular visits. In subsequent years, political extremists on both sides of the Florida Strait supported each other, as the Cuban revolutionaries based their claim for legitimacy on their struggle against Yankee imperialism, and as the old exiles, conversely, consolidated their political hold on Miami on the basis of intransigent anticommunism.15 With the advent of new communications and transportation technologies, other immigrant groups proceeded to build dense transnational networks with their home countries. They transferred economic resources, know-how, and cultural innovations and received, in turn, the affection of kin and local communities and, eventually, the recognition of their home states.16 Cubans remained apart. The exiles of the 1960s and 1970s would not partake in these practices, and those who dared to break rank were ostracized, if not physically attacked. Former upper- and middle-class Cubans made it a point of honor not to return to the island while Fidel Castro was still in power and not to contribute a single dollar to the support of the regime. Cuban transnationalism was effectively rescinded. The aftermath of Mariel started to transform this situation because the new refugees saw their departure as an economic strategy on behalf of their families and kin rather than principled opposition to the revolution in which they had been raised. Militant anticommunism declined and family solidarity took its place. The new refugees found ways to discreetly send money and goods to their kin and friends and to return to the island to enjoy the recognition garnered by their generosity. Their outlook and behavior did not differ much from that of other Latin American immigrants doing the same thing. With time and growing numbers, Cuban transnationalism was reborn. It emerged, however, in a bifurcated context in which the older, richer, and more politically connected segment of the community disapproved of these practices.17 The question arises at this point as to why the two segments of the Cuban expatriate community did not come to blows over the return trips and the continuous transfer of resources to Cuba, and why the old exiles’ political representatives were not more successful at preventing them. The answer is rather complex, and only a tentative explanation can be advanced here. First, the Cuban establishment in Miami, by virtue of cutting off social ties and economic support to the new refugees, had lost moral sway over them. It could not simultaneously disparage the newcomers and lecture them to stop sending remittances. Second, what the refugees were doing was perfectly understandable and in accord with the value system of traditional Cuban society, in which family loyalty was paramount. It was one thing to prevent foreign merchant

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46 : Alejandro Portes and Aaron Puhrmann vessels from arriving in Havana harbor; it was quite another to imprison fellow Cubans for trying to help their families on the island. The Cuban American political machine succeeded at the first task but failed at the second.18 The US federal government tacitly collaborated in the reemergence of Cuban transnationalism in various ways. First, it did not repeal the Cuban Adjustment Act and continued to grant Cubans who set foot on US shores quasiautomatic asylum. Second, it did not persecute too vigorously those who returned to the island or the commercial agencies that organized such trips. Even at the height of repressive regulations during George W. Bush’s administration, recently arrived refugees continued sending remittances home and travelling there through third countries. Penalties for doing so were exceptional and were all but eliminated by the Obama administration.19 The effect of these policies was to allow, unwittingly or not, the emergence of a new dense traffic across the Strait of Florida and a growing dependence of Cuban families and local communities on the generosity of the new expatriates.20 The final phase of this saga began when the Cuban government gained full consciousness of what was taking place and began to actively promote rather than just allow departures. For years, it had been selling the services of Cuban doctors, physical education instructors, and musicians to other countries. The idea, however, that the mass of refugees abroad, especially to the United States, could become a significant economic resource took hold only gradually. This new phase culminated in the decision of the Cuban government to grant passports to anyone wishing to leave the country and to extend the period of legal residence abroad to two years, not coincidentally about the time it would take a newly minted Cuban refugee to gain legal permanent residence in the United States.21 Intentionally or not, the result of the new policy would be to transform the Cuban population of the United States so that the presence and the voice of the old anticommunist elites would be reduced. The former black-and-white world of intransigent confrontation ceded its place to a new gray one in which the expatriate community effectively functions as an important source of macroeconomic stability for the government in the island. The Cuban American political machine has not become entirely toothless, however. While trips across the Strait of Florida were tacitly tolerated when they involved a few thousand individuals, a new wave of tens of thousands of new Cuban arrivals with their minds set on sending remittances and eventually returning home is likely to trigger opposition. Already the most prominent Cuban American politician, US Senator Marco Rubio, has spoken publicly about the need to bring to an end the Cuban Adjustment Act. The current phase of resurgent Cuban transnationalism may not be the final stage of this saga, although it is unlikely that it can be entirely reversed.

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A Bifurcated Enclave : 47 The Economic Effects of Post-1980 Cuban Emigration Cuban-owned firms in the United States grew nationwide from an estimated 919 in 1967 to about 37,000 in 1982 and 61,500 in 1987. Most of these were located in the Miami metropolitan area, where 75 percent of the Cuban-origin population was concentrated. Although most such enterprises were small, aggregate receipts of Hispanic firms in Miami reached $3.8 billion in 1987, a figure that exceeded by $400 million that of second-ranked Los Angeles and was three times that of third-ranked New York, despite these cities having much larger Hispanic populations.22 By 2000, the US national rate of selfemployment per thousand populations was 93.5, whereas for Cubans it reached 127.3. In 2001, there were 125,273 Cuban-owned firms in the United States, with receipts of more than $26.4 billion. Again, most of these were concentrated in the Miami–Fort Lauderdale area.23 These and related figures attest to the economic dynamism created by the Cuban enclave since its origins in the 1960s and 1970s, but then something worrisome started to happen. In 1979, Cuban families in the United States had median household incomes of $16,326 (in 1978 dollars), a figure at par with that of the American population as a whole. By 1989, the median household income of the Cuban population was $27,292, or $3,000 dollars less than the national median; the poverty rate for that year was 14.7 percent for Cubans, a figure well below that for the Mexican population, the largest Hispanic minority, but 2 percent above the national average.24 By 1999, median Cuban household incomes had reached $40,085. The figure, however, was almost $10,000 less than that for the native-born population and more than $3,000 less than the Colombian immigrant population. The Cuban poverty rate crept up to 18.2 percent, or 3 percent above the national average.25 In 2010, the downward trend accelerated. As table 3.1 shows, median Cuban household incomes in that year were $34,919. That figure was $15,000 below that for native-born households and at par with the Mexicanorigin population. The much-talked-about Cuban economic advantage relative to other Latin American groups had effectively disappeared. As also shown in table 3.1, the Cuban household poverty rate exceeded by a full 5 percentage points the native-born average. Put differently, the Cuban population of the United States overall has not advanced economically but has moved backward relative to the native-born and to other major immigrant groups. This trend is a direct result of the continuous inflow of refugees of modest human capital and few economic resources from the island. The revolutionary regime that presided over the continuous impoverishment of the country has also impoverished the expatriate community through the sustained export of its surplus population.

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48 : Alejandro Portes and Aaron Puhrmann TABLE 3.1. Median Annual Household Incomes and Poverty Rates of Largest Immigrant Nationalities, 2010 Income Persons (N)

Median household income ($)

Poverty rate (%)

269,393,845 39,955,854

50,541 46,224

14.8 18.9

Above US average (above $60,000) India 1,780,322 United Kingdom 236,840 Hong Kong 199,971 Philippines 1,777,588 Taiwan 358,460 Canada 798,649

94,907 84,819 84,657 78,692 76,893 64,478

6.8 5.8 9.3 6.0 13.0 8.9

Close to US average ($45,000–$55,000) Vietnam 1,240,542 China 1,601,147 Poland 475,503 South Korea 624,538 Colombia 636,555 Peru 428,547

52,522 52,187 51,943 50,786 47,485 47,214

15.1 17.3 8.4 15.2 14.2 12.3

Below US Average (below $43,000) El Salvador 1,214,049 Haiti 587,149 Guatemala 830,824 Mexico 11,711,103 Cuba 1,104,679 Dominican Republic 879,187 Somalia 82,454

42,515 40,969 38,778 35,254 34,919 32,253 18,391

19.0 21.5 24.8 28.1 19.6 24.3 52.9

Region/country of birth Total native-born All immigrants

Source: US Census Bureau, 2010 American Community Survey.

This downward trend is due not only to the lower average levels of education and occupational skills of the post-1980 refugee population but also to the little support and guidance received from its co-ethnics. By failing to involve the new arrivals in the enclave’s economic networks, the Miami Cuban community accelerated its economic and social bifurcation. This trend is seen more clearly when we examine patterns of entrepreneurship and its consequences in recent years. The US Census IPUMS files for the year 2000 provide data for 66,955

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A Bifurcated Enclave : 49 adults, between the ages of eighteen and sixty-five, who earned more than $500 in the Miami–Fort Lauderdale metropolitan statistical area (MSA).26 This large sample can be divided into ethnic categories of non-Hispanic white, nonHispanic black, Cuban, other Hispanic, and other. The Cuban-origin sample is composed of 12,004 cases that can be further subdivided into pre-1980 (pre-Mariel) arrivals, Mariel entrants and later arrivals, and the US-born second generation. The data for 2000 are convenient because they include a sizable number of pre-Mariel Cubans still in the labor force and because adult second-generation Cubans in that year were overwhelmingly the children of early exiles. Table 3.2 presents personal and family incomes for these ethnic categories. Results show that non-Hispanic whites (N = 25,387) occupied the top of the economic hierarchy, with incomes higher than any other group. All others had average personal incomes that were significantly lower, but of these, only pre-1980 Cubans and the US-born Cuban second generation had incomes that exceeded the mean for the metropolitan area. The trend was the same when we consider family incomes. In this case, only non-Hispanic whites and preMariel Cubans exceeded $80,000 in annual incomes, with the Cuban second generation shy of that amount by little more than $1,000. By contrast, refugees arriving during the Mariel exodus and after had not succeeded economically. Their personal and family incomes were less than other Hispanic immigrants in the area and not statistically different from non-Hispanic blacks, the bottomranking ethnic category. It could be argued that the category “1980 or after Cuban migrant” is too broad because it does not distinguish Mariel entrants and subsequent arrivals from Cubans coming later whose characteristics might be quite different. To examine this possibility, we subdivided this category into Cubans arriving in the United States between 1980 and 1989 and those coming after 1990. Results do not support the hypothesis of significant differences in the post-Mariel period. If anything, the economic profile of the most recent migrants is worse: average personal income of post-1989 Cuban migrants in the Miami–Fort Lauderdale metropolitan area was $21,313, compared to $26,330 for those arriving during the Mariel exodus and its aftermath The low incomes of more recent arrivals may be due to their recency in the country and, hence, lesser US-acquired work experience. We examine this possibility in the next section.27 Table 3.3 disaggregates the figures further into the categories of selfemployed and wage earners among adult males (there were not sufficient numbers of self-employed females to permit interethnic comparisons). The same ethnic hierarchy observed earlier holds, with non-Hispanic whites at the top, pre-Mariel Cubans close behind, followed by their children and then everyone else. As repeatedly found in prior studies, entrepreneurs (the self-employed) enjoy a substantial economic advantage in terms of personal and, especially,

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37,407 68,720 66,955

Total MSA 49,812 84,842 25,383

Non-Hispanic white a 26,642*** 51,361*** 12,003

Non-Hispanic black 45,218*** 82,589 4,914

Pre-1980 migrant 23,961*** 51,071*** 5,021

1980 or after migrant

34,971** 78,739*** 2,069

US-born

27,671*** 56,371*** 14,546

Other Hispanic

a

Non-Hispanic white is the reference category for all comparisons, significant differences from this category are noted by asterisks. ***p < .001. **p < .01.

Personal income Family income N

Racial/ethnic group

Cuban

32,724*** 59,674*** 3,019

Other

TABLE 3.2. Personal and Family Incomes of Racial and Ethnic Groups in Miami–Fort Lauderdale Metropolitan Area (age 18–65), 2000

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61,712 80,948 57,474 88,226 106,667 84,162

70,500 90,618 67,102

53,078*** 60,443*** 52,589***

18,929*** 39,255*** 28,244***

Non-Hispanic Non-Hispanic whitea black

45,010 64,968 41,639

Total MSA

87,404 n.s 105,921 n.s 82,363 n.s

56,541*** 71,302 n.s 52,523**

Pre-1980 migrant

50,109*** 53,545*** 49,410***

26,918*** 28,250*** 26,647***

1980 or after migrant

77,688*** 94,683 n.s 75,569**

29,265*** 65,594 n.s 35,983***

US-born

55,409*** 71,671*** 53,294***

32,414*** 49,033*** 30,254***

Other Hispanic

58,974*** 79,990** 55,868***

37,383*** 57,369*** 34,429***

Other

Source: Public Use Microdata Samples (IPUMS 2000). Note: Universe includes adult males age 18–64 who were not unemployed, and whose annual income was greater than or equal to $500. Person-weights used. a Non-Hispanic white is the reference category. Significant differences from this category are noted by asterisks. ***p < 0.001. **p < .01. *p < 0.05 (two tailed). n.s = nonsignificant difference.

(a) Personal income Working adults Self-employed Waged and/or salaried (b) Family income Working adults Self-employed Waged and/or salaried

Racial/ethnic group

Cuban

TABLE 3.3. Personal Incomes of Working, Self-Employed, and Waged and/or Salaried Males by Racial and Ethnic Group in Miami–Fort Lauderdale Metropolitan Area, 2000

52 : Alejandro Portes and Aaron Puhrmann family incomes. Non-Hispanic whites and pre-1980 Cuban entrepreneurs were the only groups to exceed annual family incomes of $100,000 in 2000, with the difference between both groups just shy of $1,000. They were followed, at some distance, by second-generation Cubans (the children of the earlier exiles) and then all others. Differences among waged and salaried workers followed exactly the same pattern: there was no statistical difference between the average incomes of non-Hispanic white and pre-Mariel Cuban workers, whereas all other groups fell significantly behind. This result indicates that Cuban workers who arrived at the time that the ethnic enclave emerged had done rather well economically, whether or not they were employed in Cuban firms. The difference is stark for Mariel and post-Mariel refugees, whose income levels were at the bottom of the ladder for both self-employed and waged and/or salaried workers in personal as well as in family income. Particularly noteworthy is the poor performance of entrepreneurs from this group, whose economic rewards were the lowest of all ethnic categories.28 It is clear from these results that the original advantages conferred on entrepreneurs by the Cuban enclave did not extend to post-1980 arrivals. Part of this disadvantage was due to their recency, a possibility that we examine next. However, secondgeneration Cubans entered the local labor force at about the same time; that is, they were also “recent” workers with little work experience. Yet their economic performance as both entrepreneurs and workers far exceeded that of their Mariel and post-Mariel compatriots. This lack of success was not because of lack of trying among recent arrivals. Table 3.4 presents self-employment rates for all adult men in the Miami metropolitan area by ethnic categories in 2000. Two trends are apparent in these results. First, pre-Mariel Cubans were the most entrepreneurial group, with a rate significantly higher than non-Hispanic whites. This result accords with the historical role of this group as builders of the Cuban economic enclave. Second, Mariel and post-Mariel Cubans were also strongly inclined to follow the self-employment route, with self-employment rates not significantly lower than those for non-Hispanic whites. However, as we have just seen, their efforts did not pay off economically. Multivariate Analysis: Income Determinants The average interethnic differences observed previously are significant but subject to the objection that they reflect differences in levels of human capital, including education and work experience. Some economists make much of the tendency for entrepreneurs to have higher levels of human capital, concluding that the economic gain from self-employment is a “myth.”29 More reasonably, it could be argued that pre-Mariel Cubans represent an older and, hence, more

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0.14 35,285

Self-employment N

0.18 13,780

Non-Hispanic white a 0.06*** 5,430

Non-Hispanic black 0.21*** 2,398

Pre-1980 migrant 0.17 n.s 3,077

1980 or after migrant 0.11*** 1,051

US-born

0.12*** 7,872

Other Hispanic

0.13*** 1,677

Other

Source: Public Use Microdata Sample (IPUMS 2000). Note: Universe includes adult males age 18–64 who were not unemployed, and whose annual income was greater than or equal to $500. Person-weights used. a Non-Hispanic white is the reference category. Significant differences from this category are noted by asterisks. ***p < 0.001. **p < .01. *p < 0.05 (two tailed). n.s. = nonsignificant difference.

Total MSA

Racial/ethnic group

Cuban

TABLE 3.4. Self-employment Rates among Males by Racial and Ethnic Group in Miami–Fort Lauderdale Metropolitan Area (age 18–65), 2000

54 : Alejandro Portes and Aaron Puhrmann experienced population, and that this is the root cause of their superior economic situation. For reasons of space, we restrict the presentation of results to family incomes that provide a more accurate measure of overall economic well-being. Table 3.5 presents regressions of family incomes in actual dollars for the adult working population of Miami–Fort Lauderdale on indicators of human capital, self-employment, and ethnic origins. The first model presents the effects of all ethnic categories, and the second disaggregates the Cuban-origin population into the subcategories discussed previously. Three main findings emerge from this analysis. First, education and work experience, indexed by age, have the expected strong net effects on incomes, as does gender. College and postgraduates derive an advantage from their education, measured in tens of thousands of dollars, relative to high school dropouts TABLE 3.5. Regressions of Family Income on Ethnicity and Selected Variables (age 18–64), 2000 I Ethnicity a Cuban Pre-1980 Cuban 1980 or after Cuban US-born Cuban Black Hispanic Other Female Age Age (squared) Education b High school Some college College Postgraduate Self-employed Intercept N R2

II

–9511.28***

–21608.99*** –19352.02*** –19793.26*** –1925.97*** 392.40** –0.93

212.53 n.s –23552.77*** 114.91 n.s –21912.73*** –19680.03*** –20046.82*** –2342.27*** 442.76** –1.79 n.s

7031.37*** 17832.03*** 37975.68*** 60470.47*** 14167.01*** 44109.86*** 66,955 0.12

6269.24*** 16139.94*** 36265.05*** 58872.11*** 14133.69*** 45180.10*** 66,955 0.12

Source: IPUMS 2000 (5 percent microsample). Note: Universe includes adults age 18–64 who were not unemployed and whose annual income was greater than or equal to $500. Raw N values included; personweights used. a Non-Hispanic white is the reference category. b Less than high school is the reference category. *p < .05. **p < .01 ***p < .001. n.s. = not statistically significant effect.

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A Bifurcated Enclave : 55 (the reference category). Women experience the well-known income handicap relative to statistically equivalent males. Second, after controlling for these predictors, self-employment continues to have a positive and significant effect. Compared to workers with the same education, work experience, gender, and ethnicity, the self-employed have a net annual income advantage of $14,000 in this sample. Third, all ethnic categories earned significantly less than non-Hispanic whites, even after controlling for human capital, gender, and self-employment. These differences are statistically significant in the first model but disappear when the Cuban-origin sample is disaggregated. Pre-Mariel Cubans and the US-born Cuban second generation now exhibit incomes that are higher than those of comparable non-Hispanic whites, although the differences are not statistically significant. In contrast, post-Mariel Cubans continue to experience an income disadvantage that is higher than that of any other ethnic category, including African Americans. The annual income gap relative to statistically comparable native whites was a startling $23,000 for this segment of the Cuban population. A possible objection to these findings is that age is not a good indicator of US work experience. Mariel and post-Mariel entrants of the same age as pre1980 Cubans may have had much fewer years of experience in the US labor market because of their recency of arrival. To take into account this possibility, we substituted actual US work experience for age across all ethnic groups. For the native born, work experience is computed in standard fashion as age less education less 6. For adult immigrants, it is years since US arrival minus y, where y is 0 for those who arrived after age eighteen and (eighteen minus age at arrival) for those who arrived as minors. Table 3.6 presents the result for the adult universe and for males only. Adding work experience to the equation, results are even more powerful than before. The Cuban second generation remains statistically indistinguishable from non-Hispanic whites, although they receive slightly lower average incomes. In contrast, pre-Mariel Cuban males exceed the incomes of the reference category by a significant margin. Net of work experience and other control variables, this group of earlier exiles displayed a net income advantage over native white males of almost $4,000 in 2000. By 2010, the number of pre-1980 Cubans in the Miami MSA labor force had dwindled considerably and the figures for the US-born second generation were no longer limited exclusively to their children. Still, the trends noted for 2000 held. Table 3.7 presents family incomes for the same ethnic categories for the Miami–Fort Lauderdale MSA in 2010. The same rank order among groups is evident. For the adult male population as a whole and for the self-employed, pre-Mariel Cubans come next to non-Hispanic whites in annual incomes, and the differences between the two categories are not statistically significant.

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56 : Alejandro Portes and Aaron Puhrmann TABLE 3.6. Regression of Family Income on Ethnicity and Selected Variables Substituting Work Experience for Age, 2000

Ethnicity Pre-1980 Cuban 1980 or after Cuban US-born Cuban Black Hispanic Other Female Work experience (US) Work experience (squared) (US) Education b High school Some college College Postgraduate Self-employed Intercept N R2

Adults (18–64)

Males (18–64)

2023.88 –14956.88*** –222.71 n.s. –19062.42*** –14163.78*** –14091.57*** –2408.99*** 940.46*** –15.81***

3849.55* –16442.62*** –372.66 n.s –17100.27*** –15565.28*** –15856.60***

5787.45*** 15452.91*** 36585.79*** 60334.30*** 14869.66*** 50467.92*** 66,955 0.13

5109.78*** 14750.29*** 37062.47*** 66736.50*** 15281.24*** 49398.98*** 35,285 0.15

a

934.68*** –13.00***

Source: IPUMS 2000 (5 percent microsample). Note: Universe includes adults age 18–64 who were not unemployed, and whose annual income was greater than or equal to $500. Raw Ns included; person-weight used. a Non-Hispanic white is the reference category. b Less than high school is the reference category. *p < .05. **p < .01. ***p < .001.

The US-born Cuban second generation follows and then everyone else. The “other” category, which comprises mostly Asians, had slightly higher selfemployment income than the Cuban second generation. Despite the additional decade that had elapsed since 2000, post-Mariel Cubans still trailed by a wide margin. Their annual incomes are slightly more than half those of their older compatriots and lower than those of African Americans. Table 3.8 presents regressions of 2010 family incomes on the same array of predictors used previously. In this case, however, we break down the Mariel and post-Mariel category into Cubans arriving in the 1980s and those coming in the 1990s and afterward. With work experience controlled, results are more powerful than before showing that post-1989 Cubans had the lowest average family incomes, far below native blacks. Mariel and post-Mariel arrivals also continue to display a significant disadvantage. Pre-1980 exiles are not statistically different from native whites, but as indicated previously, their numbers

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79,797 83,357 78,051

Working adults Self-employed Wage and/or salaried

101,697 115,401 98,004

Non-Hispanic white a 63,147*** 60,929*** 63,394***

Non-Hispanic black 98,508 n.s. 95,179 n.s. 99,471n.s.

Pre-1980 migrant 56,887*** 56,549*** 56,987***

1980 or after migrant

US-born 90,820** 88,291* 91,283 n.s.

Source: 2010 American Community Survey. IPUMS microdata sample. a Non-Hispanic whites is the reference category. Statistically significant differences from it are noted by asterisks. *p < .05. **p < .01. ***p < .001. n.s. = not statistically significant difference.

Total MSA

Racial/ethnic group

Cuban

64,349*** 64,543*** 64,318***

Other Hispanic

TABLE 3.7. Family Incomes of Working, Self-Employed, and Waged and/or Salaried Males by Racial and Ethnic Group in Miami–Fort Lauderdale Metropolitan Area, 2010

83,937*** 89,049*** 83,337**

Other

58 : Alejandro Portes and Aaron Puhrmann TABLE 3.8. Regressions of Family Income on Ethnicity and Selected Variables Substituting Work Experience for Age, 2010

Ethnicity a Pre-1980 Cuban 1980–1989 Cuban 1990 and after Cuban US-born Cuban Black Hispanic Other Female Work experience (US) Work experience (squared) (US) Education b High school Some college or associate’s degree College Postgraduate Self-employed Intercept N R2

Adults (18–64)

Males (18–64)

1156.69 –14301.99*** –30636.59*** 4687.64* –24230.51*** –19709.82*** –10918.04*** –4887.57*** 431.46*** –8.14**

2367.85 –14851.41*** –30803.23*** 638.53 –22658.45*** –22159.07*** –14375.35***

8988.26*** 21165.30*** 45677.36*** 77829.09*** 3035.84* 57570.90*** 27,192 0.14

8313.39*** 20146.45*** 45958.75*** 82176.93*** 3957.43* 57785.77*** 13,537 0.15

510.35** –10.50**

Source: American Community Survey, 2010. a Non-Hispanic white is the reference category. b Less than high school is the reference category. p