Guide A History of Organized Labor in Bolivia

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Conscious of the remarkable upheavals which punctuated Bolivian history during the twentieth century, Alexander traces the relative successes of Bolivia's labor.
Table of contents

Note: The averages are calculated using survey weights and all imputed data.

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To determine the effects of unions on productivity, the starting point is the model developed by Brown and Medof f This is a variant of a Cobb-Douglas production function that distinguishes between two types of workers nonunion and union. Assuming constant returns to scale, the production function can be written as follows:. After some manipulation, equation 1 can be linearized and written as:. Because equation 2 is rather restrictive a more flexible specification is used, following a general form of a translog specification for the production function Christensen, Jorgenson, and Lau, After including an error term, and additional controls for productivity, the specification to be estimated can be written as follows:.

Although similar specifications have been widely used in the literature, there are limitations that need to be discussed for details on the discussion see Brown and Medoff and Hirsch and Addison First, while physical production is preferable, in its absence, this paper uses value added. Following Hirsch , this problem is mitigated by controlling for industry fixed effects and measures of market competition.

A second problem is that the specification assumes union and nonunion establishments share the same production function, except for the productivity parameter associated to unions. Although this problem could be alleviated by introducing different set of interactions, it may require more information than what is available. In addition, the flexibility obtained using a translog production function equation 3 should help reduce the severity of the problem.

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The most vexing problem is the potential endogeneity of establishment unionization. According to Clark , one might not expect unionization and sales to be simultaneously determined, since unionization should have happened long before the survey interview. Concerns with respect to the inter-temporal effects of unionization remain. If union negatively affects profits, businesses will be less likely to survive.

This survivor bias should lead to overstate union productivity effects since businesses with detrimental union effects on performance are least likely to remain in the sample Addison and Hirsch Further, omitted variables in the specification can also generate inconsistent estimates if the unobserved characteristics have systematic variations between union and nonunion establishments. Taking advantage of the rich information contained in the survey, the preferred specifications controls for different characteristics such as age of the establishment, manager experience and ownership characteristics, among others, that provides a flexible specification, reducing the impact of otherwise unmeasured characteristics.

Nevertheless, because of potential survivor bias and the presence of additional unobserved factors, the estimations could be upward biased, should be considered with care, and should not be interpreted as causal effects. To test the sensitivity of the productivity estimates to the controls, different specifications are used to control for aspects related to market competition, establishment characteristics and organization, and innovation policies.

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  • Following the specification shown in equation 3 , the natural logarithm of value added per worker is used as the productivity measure. For observations where production costs exceed the value of total sales, total cost is constrained and the cases controlled using a dummy variable. The main variable of interest, union density, is included as a share between 0 and 1, which indicates what share of the permanent labor force in the establishment is unionized.

    P-values in parentheses. All models are estimated using sample weights.

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    All models include region and broad industry fixed effects. Table 5 presents the results of the basic specification which controls only for production factors, and region and industry fixed effects.

    These basic results show that for most countries in our sample, unions have a positive but weak correlation with productivity. In the absence of endogeneity, the point estimates indicate that, on average, if a nonunion establishment unionizes it could increase productivity per worker between 0. The only exception is Argentina; the estimate shows that unions have a large negative and significant impact on productivity Given the type of production function used here, the coefficients for capital and labor are more difficult to interpret than in the standard Brown and Medoff model.

    To facilitate interpretation, at the bottom of Table 5 , the derivatives with respect to labor and capital are obtained and evaluated at the mean.

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    In Argentina, Panama and Uruguay, however, the estimates are somewhat unexpected as the marginal effect of capital is almost zero, with a positive marginal effect from labor. Although these results are worrisome, they remain consistent across different specification, and should not to be crucial for the main focus of the analysis.

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    The basic model estimated in Table 5 does not take into account other characteristics that can explain productivity or that can differ between unionized or nonunionized establishments. Tables 6 and 7 present estimations using richer specifications. Table 6 presents results of the union productivity effect only, to show how sensitive the estimates are to additional controls, while Table 7 presents the results of the full specification model.

    Controlling for the level of competition should improve the estimates by partially accounting for differences in prices caused by union effects on labor costs.

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    The second row of in Table 6 provides the estimates after controlling the number of competitors the in the market. In Chile and Uruguay, the productivity estimates are greatly reduced, with the estimates for Uruguay becoming negative. In Chile, these results seem to be driven by the impact that some competition competitors in the market has on sales and productivity see Table 7. In Uruguay, while partial model not shown here suggests a story similar to Chile, after controlling for other factors, competition seems to have a small and not significant impact on productivity.

    Longer hours of operation or greater use of production capacity can spuriously increase productivity estimates if they are not controlled for. Likewise, if establishments subcontract production to smaller units, or generate sales via services rather than manufacture , it may bias the productivity estimates. Results in Table 7 show the results controlling for level of utilization of capital, weekly hours of operation, and sales structure services and subcontracts.

    Controlling for these productivity adjustments suggests that union productivity enhancements are not coming from more intensive use of production factors, showing larger estimates increase for all countries. Chile and Uruguay show the most drastic changes on productivity, with modest changes elsewhere. The results in Table 7 show that the parameters for these controls are consistent with the expected signs.

    Other factors correlated with union status and productivity are linked to establishment characteristics and management quality. To account for establishment characteristics, variables controlling for years of operation, whether the establishment is part of a larger firm, and if it the establishment is owned by foreign capital are included in the specification.

    According to the results in Table 7 , the fall in the union-productivity relationship in Bolivia is explained because most of the positive relationship was driven by foreign owned companies, which are typically unionized. This is consistent with the fact that being part of a larger firm and being owned by foreign capital is correlated with better managerial policies Aitken, et al.

    Alternatively, in Chile, not accounting for younger establishments, which are more productive and less likely to be unionized, was understating union productivity effects. To control for management quality and organization, variables describing the ownership structure and management characteristics are included in the specification. Argentina and Panama show the largest positive change in the estimates of the union-productivity relationship. These results suggest that unionized establishments have relatively more inefficient management, which puts downward pressure on productivity if management characteristics are not accounted for.

    The results in Table 7 suggest that the strong relationship between productivity and decision strength of the largest shareholder is the main factor explaining the impact on the union-productivity estimates in Panama. Although some of the previous controls are arguably not directly affected by unions, aspects such as investment, training, and workforce structure could be affected their presence. In the interest of disentangling the direct effect unions on productivity, additional controls are introduced in the specification. Under the assumption that unions have a negative impact on investment rent seeking behavior , controlling for investment should have a positive impact on the union-productivity relationship.

    The results on Table 6 , however, indicate that controlling for investment and innovation have little impact on the union estimates. Because unions are often associated with lower turnover, unionized establishments might be more likely to provide more training, since they can benefit from the returns of such investment through higher productivity Kuhn ; Allen Although human capital upgrades are legitimate sources of productivity enhancements, they may not necessary generate improvements in technical efficiency.

    Including training as a control variable in the estimations see Table 7 shows that, on average, training has a positive, mostly not significant, impact on productivity. Adding these controls to the specification has the expected negative effect on the union-productivity relationship for all countries, especially for Panama, indicating that training is an important channel through which unions improve productivity. Unions can also influence the structure and composition of the workforce within establishment, changing the mix of production factors and affecting productivity.

    Except for Chile and Panama, controlling for these effects increases the impact of unions on productivity. In Bolivia, Mexico and Uruguay, similar to the evidence at the micro level Rios-Avila and Hirsch, forthcoming , unionized establishments are associated with low-educated, low-skill workers, and not controlling for it understates productivity. The evidence, however, is insufficient to detect the effect of other workforce characteristics on union-productivity effect. Although there is limited evidence on the productivity effects of unions for these countries in the literature, the evidence that does exist appears consistent with the results found here.

    In the case of Uruguay, Cassoni, et al. These similarities increase the confidence in the results shown in Table 6. Productivity, Sensitivity to Specifications. All models are calculated using all controls specified in the previous model. All models are estimated using the sample weights, and include region and broad industry fixed effects. Productivity, Full Specification. The base categories for competition are those establishments facing none or 1 other establishment in the market.

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    For training, the base category corresponds to establishments with no training programs. For education, the base category corresponds to workers with 3 or fewer years of education for Bolivia and Mexico, 7 to 12 years for Argentina, Chile and Panama, and years of education for Uruguay. All models are estimated using sample weights, and include region and broad industry fixed effects.

    Taken as a whole, the results shown in Table 6 suggest that unions are associated with positive union-productivity effects, but that there is a lot of heterogeneity in the relationship both within and across countries the former seen by the low significance levels of results. The results also provide some evidence that the union-productivity estimates are reasonably robust in richer specifications that take into account typically unobserved establishment characteristics. On one end of the spectrum, using the preferred specification all controls , it can be observed that unions in Bolivia have no effect on productivity practically zero , while a negative and significant estimate is seen in Argentina On the other side, large positive, albeit insignificant, effects are observed in Chile and Panama, while estimates for Mexico and Uruguay are positive and consistent across specifications, but not significant.

    The evidence presented in Table 6 also brings some light on determinants of the union-productivity relationship. Controlling for productivity adjustments increases union productivity estimates. Part of the positive productivity effects, however, seem to be related to large unionization rates across large establishments, foreign owned, with typically better management. Consistent with the hypothesis in Fairris , unions seem to be improving productivity by improving job training.

    Finally, lower levels of worker human capital seem to have contributed to an understatement of the productivity effects of unions. Taken at face value, the estimate found for Argentina indicates that output per worker in a fully unionized establishment is 25 log points lower than in an equivalent nonunion establishment. Were we to have obtained such a result in other countries, it would have raised the question how union establishments could survive given lower productivity and presumably higher compensation.

    Argentina, however, is a special case compared to other countries in the region. There are very few establishments in the sample that are not unionized, and those nonunionized are rather different relatively younger and smaller.