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on Central and South America |
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Issue of 2020‒01‒27
six papers chosen by |
| By: | González-Bustamante, Bastián (Universidad de Santiago de Chile) |
| Abstract: | This chapter examines the concept of public service models with special emphasis on the Latin American reality. The following section deals with the subject from an historical perspective, its ties to the patronage systems, and the main milestones which have shaped the evolution of the civil services. Subsequently, the next section deals with the chief characteristics and changes in the civil services and presents an evaluation of the models in Latin America. Finally, the last section sets out some brief conclusions and summarises the main ideas of this entry. |
| Date: | 2018–06–16 |
| URL: | http://d.repec.org/n?u=RePEc:osf:socarx:mp4qd&r=all |
| By: | Luz A. Flórez (Banco de la República de Colombia); Leidy Gómez D. |
| Abstract: | The objective of this paper is to analyze the impact of skill mismatch on labour turnover for the case of Colombia. Our work follows the of the job matching theory of Jovanovic (1979a, 1979b, 1984). In line with this theory we find a positive relationship between skill mismatch and labour turnover (measured as the worker reallocation rate) using a panel of 23 cities for the period 2009-2017. Our results suggest that cities with a higher proportion of mismatched workers present higher worker reallocation rates. In this case one standard deviation of increment in the proportion of mismatch workers increases the WR rate around 0.12 standard deviations. This result is explained mainly by the increase on separations as is suggested by the theory. **** RESUMEN: El objetivo de este documento es analizar el efecto del desajuste en habilidades en la rotación laboral para el caso de Colombia. Nuestro enfoque teórico sigue de cerca el modelo de búsqueda de empleo propuesto por Jovanovic (1979a, 1979b, 1984). Como es sugerido por esta literatura, usando el panel de 23 ciudades para el periodo 2009-2017, encontramos evidencia de una relación positiva entre el nivel del desajuste en las habilidades y la rotación laboral, medida como la reasignación de trabajadores. Un incremento de una desviación estándar en el nivel de desajuste de habilidades produce un incremento de 0.12 desviaciones estándar en la rotación laboral. Estos resultados se explican principalmente por el incremento en las separaciones como es sugerido por el modelo teórico. |
| Keywords: | Skill mismatch, overqualification, underqualification, worker reallocation, panel data, and cross-sectional dependence, desajuste de habilidades, sobre-calificación, baja calificación, datos panel, reasignación de trabajadores, y dependencia transversal |
| JEL: | I25 J62 J63 J64 |
| Date: | 2019–12 |
| URL: | http://d.repec.org/n?u=RePEc:bdr:borrec:1099&r=all |
| By: | Christopher David Absell (Departamento de Ciencias Sociales, Universidad Carlos III de Madrid) |
| Abstract: | During the period spanning independence in 1822 to mid-century, Brazil’s southeast shifted from specialising in the export of cane sugar to coffee. This paper explores the mechanism underlying this shift by exploiting a wealth of new monthly data on the Brazilian and international coffee and cane sugar markets during the period 1827-40. I argue that the timing of the coffee boom was driven by a rapid increase in foreign market potential associated with the abolition of the tariff on coffee in the United States. I estimate that American tariff reform served to increase coffee exports and African slave imports by around one-fifth. American firms, with indirect links to the slave trade, rapidly became major players in the export market in Rio de Janeiro, while non-American firms, traditionally specialised in Continental European destinations, turned their sights on the American market. |
| Keywords: | Coffee, Brazil, slavery, tariffs, market potential |
| JEL: | N56 N76 |
| Date: | 2020–01 |
| URL: | http://d.repec.org/n?u=RePEc:hes:wpaper:0175&r=all |
| By: | Ronald Fischer; Nicolás Campos; Eduardo Engel; Alexander Galetovic |
| Abstract: | In 2016, Brazilian construction firm Odebrecht was fined $2.6 billion by the US Department of Justice (DOJ). According to the plea agreement, between 2001 and 2016 Odebrecht paid $788 million in bribes in 10 Latin American and two African countries in more than 100 large projects. The DOJ estimated that bribe payments increased Odebrecht’s profits by $2.4 billion. Judicial documents and press reports on the Odebrecht case reveal detailed information on the workings of corruption in the infrastructure sector. Based on these sources we establish five facts. First, for projects where Odebrecht paid bribes, renegotiations amounted to 71.3 percent of initial investment estimates, compared with 6.5 percent for projects where Odebrecht paid no bribes. Second, Odebrecht’s bribes were less than one percent of a project’s final investment. Third, the profits Odebrecht obtained from bribes as well as its overall profits were relatively small: around 1 to 2 percent of sales. Fourth, the creation of the Division of Structured Operations (DSO) by Odebrecht in 2006 led to major reductions in the firm’s costs of paying bribes and recipients’ costs of hiding the ilegal proceeds. Fifth, following the creation of the DSO, Odebrecht’s sales multiplied tenfold in four years, while its profits remained relatively small. We build a model where firms compete for a project, anticipating a bilateral renegotiation in which their bargaining power will be larger if they pay a bribe. If cost dispersion among firms is small, profits are small in equilibrium even when bribes are paid. When one firm unilaterally innovates by making bribe payments more efficient, its market share increases substantially while profits, which depend on cost advantages and the magnitude of bribes, remain small. A parametrization using the DOJ’s data suggests that after the creation of the DSO, Odebrecht enjoyed an almost 70 percent cost advantage in bribing. JEL Codes: H54, H57, K42. Key words: auctions,bribes,corruption,fundamental transformation.,Infrastructure,lowballin g.,renegotiations |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:edj:ceauch:345&r=all |
| By: | Eduardo Engel; Ronald Fischer; Alexander Galetovic; Jennifer Soto |
| Abstract: | Risk allocation is an essential component of a successful public-private partnership contract financed with user fees. For many of these projects, demand risk is large and mostly exogenous. This suggests that we evaluate contract designs that do not force the concessionaire to bear risk it cannot manage. In this paper we study present-value-of-revenue (PVR) contracts, which have this property. Under a PVR contract, the regulator sets the discount rate and the tariff schedule and firms compete on the present value of tariff revenue. The lowest bid wins and the contract lasts until the winning firm collects revenue equal to its bid. We provide a theoretical analysis comparing debt financing under a fixed term concession and PVR. We show that, other things equal, debt is less risky under PVR, particularly against large systemic shocks, and therefore debt-to-capital ratios can be higher. In addition, we show that the view that PVR does not mesh easily with fixed maturity debt is wrong. The reason is that demand realizations are independent of contractual forms. Finally, we analyze the experience with PVR contracts, considering two early examples from the UK and close to thirty PVR contracts for highways and airports in Chile. We conclude that PVR contracts have been at least as attractive to lenders than their fixed term counterparts. We also provide evidence of better incentives under PVR, in particular, a significant reduction of contract renegotiations. JEL Codes: H44, R42. Key words: default risk,fixed term contract,flexible term contract,Infrastructure concession,prepayment risk,project finance. |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:edj:ceauch:346&r=all |
| By: | Felipe Leal; Carlos Molina; Eduardo Zilberman |
| Abstract: | In this paper, in line with Medeiros et al. (2019) for the US, we apply Machine Learning (ML) methods with Big Data to forecast the total and underlying CPI inflation in Chile. We show that the ML methods do not gain in the inflation projection for the Chilean case in a consistent way on simple and univariate linear competitors such as the AR, the mean and the median of the past inflation, which have proven to be highly competitive. In fact, these are the winning methods in many cases. A second contribution of this work is the construction of a large dataset with macroeconomic variables related to the Chilean economy similar to McCracken and Ng (2016), who built (and maintains) a similar data for the United States. |
| Date: | 2020–01 |
| URL: | http://d.repec.org/n?u=RePEc:chb:bcchwp:860&r=all |