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The growing displacement of theory and other forms of wide-ranging knowledge of social phenomena by empirical research methods in economics is widely noted by economists and historians of economic knowledge. Less attention has been devoted, however, to understand the materialization of such changes in the scientific practices. This article studies the recent transformations in the epistemological practices at CEDE, a research center in Colombia. I use a machine learning technique called Topic Modeling, interviews to CEDE researchers, and exegesis of papers to characterize a shift in the production of knowledge in microeconometrics at CEDE during the years 2000 and 2018. I explain this shift by characterizing two sets of epistemological practices that implies a recent tendency to disdain research that cannot make a “strong” causal inference.

The purpose of this study is to account for a recent non-mainstream econometric approach using microdata and how it can inform research in business administration. More specifically, the paper draws from the applied microeconometric literature stances in favor of fitting Poisson regression with robust standard errors rather than the OLS linear regression of a log-transformed dependent variable. In addition, the authors point to the appropriate Stata coding and take into account the possibility of failing to check for the existence of the estimates – convergency issues – as well as being sensitive to numerical problems.

The author details the main issues with the log-linear model, drawing from the applied econometric literature in favor of estimating multiplicative models for non-count data. Then, he provides the Stata commands and illustrates the differences in the coefficient and standard errors between both OLS and Poisson models using the health expenditure dataset from the RAND Health Insurance Experiment (RHIE).

The results indicate that the use of Poisson pseudo maximum likelihood estimators yield better results that the log-linear model, as well as other alternative models, such as Tobit and two-part models.

The originality of this study lies in demonstrating an alternative microeconometric technique to deal with positive skewness of dependent variables.

The paper aims to present an analysis of the indirect and direct effects of active labour market policy measures at the regional level for Western Germany.

Most evaluation studies of active labour market policy focus on the microeconometric treatment effect using individual data and do not account for possible indirect effects like deadweight and substitution effects. The present study uses a dynamic specification of the augmented matching function at the regional level. A dynamic panel data model is estimated using monthly and regional variation of different labour market programmes as explanatory variables. Furthermore, spatial interactions are taken into account by adding a spatially correlated error term.

Almost no significant negative effects are found of the stock of participants in programmes of labour market policy on the number of outflows from unemployment into regular jobs. Thus, contrary to findings at the individual level, no lock‐in effect is found. The number of programme participants does not reduce the number of outflows from unemployment. On the other hand when looking not at the stocks but on the outflows from programmes, no positive effects on outflows from unemployment at the regional level are found.

Because of data limitations only a period up to six months after completing a programme is used.

The authors distinguish between the effects of the stock of programme participants and of the outflows from programmes. Furthermore, the authors account for spatially correlated error terms by using a GM estimator proposed by Mutl in 2006.

This paper aims to evaluate the impact of the “Postliteracy” program on the qualification of beneficiaries for socioeconomic integration. This qualification is achieved first through the consolidation of the achievements of individuals freed from illiteracy, and then through their support in creating income-generating activities by providing them with technical, economic, legal and institutional knowledge to ensure their conscious and responsible participation in local and regional development efforts.

To evaluate the impact of the “Postliteracy” program, this paper uses quasi-experimental methods with a control group (participants of the “Literacy” program 2020 / 2021) and a treatment group (participants of the “Postliteracy” program 2021 / 2022). Skill acquisition is measured through pretest and posttest evaluations using a questionnaire aligned with the National Agency for the Fight Against Illiteracy (ANLCA)-adopted curriculum. The survey occurred at the beginning and at the end of the program, providing sufficient time for skill development. The questionnaire includes three sections covering socioprofessional characteristics, technical and economic domains and legal and institutional aspects. These sections contribute to a score reflecting the acquired skills for successful socioeconomic integration.

The results of the study demonstrate that the “Postliteracy” program has a positive impact on the acquisition of competences necessary for improved socioeconomic integration of the beneficiaries. The various matching techniques reveal a score difference ranging from 12 to 14 points in favor of program participants compared to those who did not participate. The Difference-in-Differences method confirms the positive and significant impact of the program.

The findings highlight the importance of the “Postliteracy” program in national literacy policy, underlining the need to further strengthen its presence within the programs deployed by ANLCA, notably by increasing the number of beneficiaries targeted by this program. To achieve this, it would be advisable to increase the funds allocated to it within ANLCA's budget.

The originality of this work is a unique research of the case of Morocco based on a microeconometric study for which the authors evaluate the impact of adult education by applying impact evaluation methods in the field of adult literacy.

In this chapter, we evaluate the employment effects of job-creation schemes (JCS) on the participating individuals in Germany. JCS are a major element of active labour market policy in Germany and are targeted at long-term unemployed and other hard-to-place individuals. Access to very informative administrative data of the Federal Employment Agency justifies the application of a matching estimator and allows us to account for individual (group-specific) and regional effect heterogeneity. We extend previous studies for Germany in four directions. First, we are able to evaluate the effects on regular (unsubsidised) employment. Second, we observe the outcomes of participants and non-participants for nearly three years after the programme starts and can therefore analyse medium-term effects. Third, we test the sensitivity of the results with respect to various decisions that have to be made during implementation of the matching estimator. Finally, we check if a possible occurrence of a specific form of ‘unobserved heterogeneity’ distorts our interpretation. The overall results are rather discouraging, since the employment effects are negative or insignificant for most of the analysed groups. One exception are long-term unemployed individuals who benefit from participation at the end of our observation period. Hence, one policy implication is to address the programmes to this problem group more closely.

Purpose – This chapter investigates vulnerability to poverty in the Republic of Haiti.

Methodology – We use a hierarchical modeling technique to allow the assessment and decomposition of vulnerability to poverty by exploiting the short-panel structure of nested data in a cross section.

Originality – Specifically, a three-level hierarchical model with a partially Bayesian restricted maximum likelihood is used in the estimation procedure. This is novel in this literature.

Findings – The decomposition method adopted in this chapter reveals that vulnerability in the Republic of Haiti is largely a rural phenomenon and is correlated negatively with schooling. The results also disclose the lack of equality in various aspects of circumstances or opportunities, including education, as the salient factor determining the status and level of vulnerability of households. Most importantly, among the different shocks affecting household's income, it is found that meso-level shocks are in general far more important than covariate shocks. This finding points to some interesting policy implications in terms of decentralizing policies and delegating more powers and providing better means to local governments to enhance household resilience to shocks and to alleviate their vulnerability to poverty.

Compares the evaluation methods of vocational training public programs. Studies the US case, the other national cases (mostly OECD countries), and the European Union case. Suggests that OECD countries, and especially the EU, should follow the US trend, and make impact microeconometric studies, in order to assess the training effects of those programs; thus, it will be possible to conduct better policies, and to spend public money in better ways. Additionally tries to explain why the USA is much more advanced in those studies than the EU and other countries; links the reasons to scientific history and to the administrative actions. Finally, presents some ideas about the Portuguese case, which is a fine example of the problem.

Analyses Polish active labour market policy programmes (ALMP) from a macroeconomic (regional) point of view. The effects of training programmes on the outflows from unemployment into employment and the effects of all ALMP programmes on the outflows from employment into unemployment (to identify displacement effects) are estimated. The empirical evidence gives no support to the view that public training programmes can be used to reduce unemployment, and there is no robust evidence for displacement effects by any ALMP programme. The result that start‐up loans can reduce flows from employment into unemployment is only weakly significant.

The purpose of this paper is to investigate whether there are any differences in the capitalization speed‐of‐adjustment across regulatory capitalization buckets of commercial banks in the USA, for the period 2002‐2009.

The Federal Deposit Insurance Corporation (FDIC) monitors banks' capital ratio using the bucketing approach. Thus, this discrete and ordered variable is modeled in the context of a partial adjustment specification, controlling for initial conditions and cross‐sectional heterogeneity. Parameters are estimated with the generalized dynamic random effects ordered probit technique that is flexible enough to allow for differential effects of covariates across capitalization categories.

The main result is that the speed of adjustment is monotonically increasing for banks belonging in lower capitalization buckets, after controlling for bank‐specific capitalization determinants. In addition, substantial differential impacts of capitalization drivers across regulatory buckets are uncovered.

This an important finding both for regulators and market participants since it sheds light on a very crucial aspect of banks' behaviour.

This is the first paper that adopts the FDIC bucketing in the actual modelling. In addition, it uses the generalized dynamic random effects ordered probit technique in order to explore potential differential impact of capital ratio determinants across buckets.