Party membership, social ties and upward mobility in Cuba

Notes

1. In the literature on the Cuban economy, it is common to find the distinction between two production sectors: the so-called ‘emerging’ one and the ‘traditional’ one (see, e.g., CEPAL 2000; Hidalgo de Los Santos and Doimeadios 2003; Hidalgo de Los Santos et al. 2002; Marquès Pereira and Théret 2002; Barbería 2008; Espina-Prieto 2001; Tulchin et al. 2005).

2. Conventionally, this classification distinguishes between activities in which new types of incentive have been applied, presumably material or monetary advantages for workers linked to exports or to the domestic dollar market (‘emerging’), and those which remain governed by incentives and leadership criteria applied prior to the crisis (‘traditional’). (Espina-Prieto 2001: 32)

3. In a nutshell, this duality is a result of two interrelated factors: the reorientation of production capacities towards import substitution and tourism since the collapse of the socialist block which opened the ‘special period’ in the early 1990s and the legalisation of the dollar in the middle of this decade (see also Domínguez 2004).

4. Job applicants for a job in mixed companies must sign a contract with the state employment agency. The employment agency will pay the workers in Cuban pesos (CUPs), on the basis of the minimum wages approved by the Labour Ministry for the authorised jobs.

5. The Centro de Investigaciones Psicológicas y Sociológicas (CIPS) is a centre for investigation belonging to the Ministry of Science, Technology and Environment.

6. In social mobility studies, there are two distinct research programmes: the so-called class analysis tradition and the so-called status attainment tradition. They distinguish each other in virtue of their diverse assumptions, use of different ranking schema (e.g., class structure vs. social position hierarchy, respectively) and different statistical techniques (grossly, log-linear models vs. analysis route). Consequently, each one has elaborated diverse interpretations and explanations of own research results. According to Marshall (1998), the distinction between status attainment and class analysis is useful for heuristic purposes because it casts light on contrasting results and disputes within social mobility literature. The distinction between status attainment and class analysis programs is beyond the scope of this article.

7. According to various scholars, three main types of policies generally enforced by socialist governments cause the relaxation of class-based inequalities in life chances. They are (1) the abolition of private property and, by implication, the abolition of some forms of direct occupational inheritance; (2) the enforcement of an educational system ruled by the State that extensively pursues the reduction of educational inheritance (e.g., introducing quota systems that favoured children of working-class parents); (3) the enforcement of equalising income policies and of a universalistic provision system (Parkin 1971; Krymkowski 1991; Collins and Coltrane 1985). On the other side, socialist policies and institutional agencies aiming at controlling the labour supply contribute to the strengthening of the link between attained education and social position attainment. Socialist governments often have created institutionalised agencies (1) to allocate students at the end of their educational career in job positions consistent with their educational qualification and (2) to enforce some restrictions on job changing during one's career (I. Szelényi et al. 1994; Krymkowski 1991; Goldthorpe 2007).

8. In contrast with capitalism system, in socialism system (1) most, if not all means of production, are collectively (usually state) owned; (2) markets are restricted to a marginal role and the logic of economic integration is based on redistribution through central planning; and (3) rationality is substantive, therefore, the provisioning for needs is according to some ultimate values, for example, equality and social justice (I. Szelényi et al. 1994).

9. The so-called market transition theory posits (Nee 1989) that the introduction of market institutions leads to (1) a decline of the advantage of redistributive power and other forms of political capital relative to non-state economic actors who possess market power; (2) higher returns to human capital than under a centrally planned economy; and (3) new opportunities centered on market activities, for example, entrepreneurship. (Cao and Nee 2000: 1175–176) Empirically, the predicted decay of advantages enjoyed by cadres when a planned economy opens up to the market has been found in Hungary (S. Szelényi 1998) and rural China (Nee 1989, 1991; Parish et al. 1995), but not in many other post-socialist societies and in urban areas of China where (prior) Party membership continues to influence the attainment of highly remunerative occupations (see, e.g., Bian and Logan 1996; Hauser and Xie 2005; Nee 1996; Nee and Cao 1999; Parish and Michelson 1996; I. Szelényi and Kostello 1996; Walder 1996; Xie and Hannum 1996).

10. UJC is the acronym of the Youth Communist Union. The upper age limit to belong to UJC is 30 years.

11. As professional and technicians positions accrue a great part of Party members, it cannot be excluded that a part of supportive people even though remained stuck in traditional sectors have been to some extent rewarded with the access to job missions abroad. Job mission abroad opportunities have increased by virtue of the international agreements for the export of professional services developed after the rise of Hugo Chavez in Venezuela and from the favourable political scenario in Latin America.

12. Data were collected from May 2010 to January 2011 in La Habana and Varadero, by Cuban students and professors as part of a broader research project designed to explore living standards and social life among diverse occupational groups for whom the reforms had brought differential income rewards in today's Cuba. To ensure having a sufficient number of cases for analysis in each occupational group, I used a quota sampling procedure that over sampled workers in emerging sectors. To avoid subjectivity, we adopted random procedures for sampling neighbourhoods and for sampling individuals within two groups.

13. In a nutshell, logistic regression is an extension of the more familiar linear regression (cf. Field 2009: 265). While linear regression is used to predict the value of a continuous variable (e.g., income), logistic regression allows us to predict categorical outcome (e.g., being a Party member or not) based on predictor variables which can be continuous or categorical (ibid.). More specifically, logistic regression is used to predict the odds of an outcome (which of two categories a person is likely to belong) given known values of predictors (Xs). The odds are defined as the probability that a particular outcome is a case divided by the probability that it is a non-case. Despite their similarity, the model of logistic regression, however, is based on quite different assumptions about the relationship between dependent and independent variables from those of linear regression. One of the assumptions of linear regression is that the relationship between variables is linear. When the outcome variable is categorical, this assumption is violated (in particular, the residuals cannot be normally distributed. For further details, see, e.g., Berry 1993). One way around this problem is to transform the data using the logarithmic transformation (Field 2009: 267). This logarithmic transformation (called the logit or log-odds) is a way of expressing a non-linear relationship in a linear way. The predicted values of the logit are retransformed into predicted odds via the inverse of the natural logarithm, namely the exponential function.

14. The odds ratio is a measure of effect size, describing the strength of association between two categorical variables (namely between the dependent and independent variables). A ratio between odds quantitatively describes the association between the presence/absence of ‘Y’ (the independent variable, e.g., hold a remunerative job) and the presence/absence of ‘X’ (independent variable, e.g., belonging to the Party) for cases (in this case, individuals) in the statistical population (in this case, Cuban workers). In other words, the value of the odds ratio is an indicator of the change in odds resulting from a unit change in the predictor (Field 2009: 270). Odds ratios are similar to the b coefficient in logistic regression but easier to understand, especially when the predictor variables are categorical. In fact, unlike b coefficient odds ratios do not require a logarithmic transformation (cf. Field 2009: 270–1) and has greater intuitive appeal. Diverse statistical software provides results from logistic regression directly as odds ratio because their use is very common (the Stata command is ‘logit depvar [indepvars], or’). In mathematic terms, the odds ratio can be derived in two ways. First, it is obtained by taking the antilogarithm of the b coefficient (see MacKinnon 2008: 300). Second, it can be calculated by taking a table 2 × 2 and obtaining the product of a pair of cells (cells a and b), and dividing this product by the product of the other pair of cells (cells b and c) – (for an easy and intuitable explanation in Spanish, see, e.g., http://networkianos.com/odd-ratio-que-es-como-se-interpreta/). About the interpretation of results, as well known, if the value of the odds ratio is greater than 1 then as the predictor increases, the odds of the outcome occurring increase. Conversely, a value less than 1 indicates that as the predictor increases, the odds of the outcome occurring decrease.

15. In addition, the second model, with the main predictors included, fits the data better. This is because the likelihood-ratio (LR) test performed by estimating two models and comparing the fit of one model to the fit of the other as it is LR χ² = 12.49; degrees of freedom = 2.

16. There is evidence that Party affiliation is a prerequisite for the attainment of administrative occupations. Consequently, I excluded administrators from the sample in order to be sure that results are not seriously affected. Running this model on a sub-dataset from which administrators are excluded, the results (not shown) indicate once again that as an individual belongs to the Party, the odds of being a worker in emerging sector rather than in traditional sector decrease. In results obtained by running model on complete dataset, the odds ratio of predictor Party member is 0.29, while in results obtained by running model on dataset in which administrators were excluded the odds ratio of the same predictor (Party member) is 0.34. Given the trivial difference, I preferred to show results obtained by running the models on the complete dataset.

17. Conversely, less than 13 per cent of individuals attained their job position by utilising weak ties – this percentage is almost identical in both groups.