Preventing rather than punishing: An early warning model of malfeasance in public procurement

Is it possible to predict malfeasance in public procurement? With the proliferation of e-procurement systems in the public sector, anti-corruption agencies and watchdog organizations have access to valuable sources of information with which to identify transactions that are likely to become troublesome and why. In this article, we discuss the promises and challenges of using machine learning models to predict inefficiency and corruption in public procurement. We illustrate this approach with a dataset with more than two million public procurement contracts in Colombia. We trained machine learning models to predict which of them will result in corruption investigations, a breach of contract, or implementation inefficiencies. We then discuss how our models can help practitioners better understand the drivers of corruption and inefficiency in public procurement. Our approach will be useful to governments interested in exploiting large administrative datasets to improve the provision of public goods, and it highlights some of the tradeoffs and challenges that they might face throughout this process.     

Estimation and model selection based inference in single and multiple threshold models

This paper evaluates the properties of a joint and sequential estimation procedure for estimating the parameters of single and multiple threshold models. We initially proceed under the assumption that the number of regimes is known á priori but subsequently relax this assumption via the introduction of a model selection based procedure that allows the estimation of both the unknown parameters and their number to be performed jointly. Theoretical properties of the resulting estimators are derived and their finite sample properties investigated.     

Specification via model selection in vector error correction models

This paper proposes a model selection approach for the specification of the cointegrating rank in the VECM representation of VAR models. Asymptotic properties of estimates are derived and their features compared with the traditional likelihood ratio based approach.     

High ownership concentration and exporting of emerging market firms: evidence from Peru

Despite the extraordinarily high ownership concentration widely observed in emerging market firms as a result of institutional voids, there is little research on how this high ownership concentration affects the exporting behavior of emerging market firms. From principal–agent and institutional perspectives, we hypothesize that high ownership concentration has a negative relationship with export intensity, because, in emerging markets, highly concentrated ownership bridges the interests of owners (principals) and managers (agents) so that principals must be prudent in exploring risky international markets. Moreover, we hypothesize that export country diversification strengthens the relationship between ownership concentration and export intensity, because broad geographic dispersion increases risk exposure and principal-agent problems. Empirical analysis based on a panel dataset for publicly listed firms in Peru from 2005 to 2014 supports the hypotheses. The study highlights the risk aversion attitude activated by ownership concentration, an attitude that protects emerging market firms from overconfidently exploring international business opportunities. The study extends the conventional literature on the interface between ownership concentration and international business in an emerging market context. We also discuss the generalizability of the findings to other emerging markets, e.g. China.     

Methods and Tools for Bayesian Variable Selection and Model Averaging in Normal Linear Regression

In this paper, we briefly review the main methodological aspects concerned with the application of the Bayesian approach to model choice and model averaging in the context of variable selection in regression models. This includes prior elicitation, summaries of the posterior distribution and computational strategies. We then examine and compare various publicly available R‐packages, summarizing and explaining the differences between packages and giving recommendations for applied users. We find that all packages reviewed (can) lead to very similar results, but there are potentially important differences in flexibility and efficiency of the packages.     

Oil Prices: Governance Failures and Geopolitical Consequences

This article links two major areas of work on the geographies of oil: socially produced scarcity and the ‘new realities’ of oil, with wider geographical inquiries, mainly global energy governance. It explores how in the current context characterised by oversupply, power stands out as a key factor in the geopolitics of prices, the interactions amongst energy institutions, the role of supply and demand, and the preferences of the actors involved. Geopolitical approaches find a niche in the gaps left by the increasing complexities of global energy governance. In this regard, energy geopolitics may be thought of as ‘governance by other means’, an alternative to failed external energy governance solutions. The article then focuses on the consequences of the drop in oil prices on producer countries and how it will impact the major issues that dominate the literature on energy security. It concludes by stating that there is a need to rethink the geopolitics of energy security in order to incorporate the global governance institutions’ failure to facilitate cooperation as another cause of the re-securitisation of energy policies.     

Latin American Cycles: Has Anything Changed After the Great Recession?

This paper analyzes the evolution of growth cycles and business cycles in Latin America from 1980 to 2013 by using monthly industrial production. Focusing on both synchronization and other cyclical features, we find evidence of significant cyclical links between the countries of the region, which seem to be highly integrated in this period. Notably, we find that the Great Recession did not lead to any significant impact on the preexisting Latin American cyclical linkages.     

Unions, monetary shocks and the labour market cycle

This paper provides a new growth model by considering strategic behaviour in the supply of labour. Workers form a labour union with the aim of manipulating wages for their own benefit. We analyse the implications on labour market dynamics at business cycle frequencies of getting away from the price-taking assumption. A calibrated monetary version of the union model does quite a reasonable job in replicating the dynamic features of labour market variables observed in post-war U.S. data.