Latin American Journal of Central Banking最新文献

This paper investigates the relationship between expansionary credit events and firms’ employment decisions. To overcome the endogeneity coming from the supply side of credit we exploited the legal and political framework in Mexico to examine the effects of local governments’ prepayment of loans, a situation that leads banks to channel newfound liquidity in firms. Analysis of a novel data set covering a 10-year period showed that a 1-standard-deviation increase in the issuance of new loans increases firms’ employment by 2.57 percentage points. Timing of the boost in employment varies, with smaller firms reacting immediately and larger firms reacting four months later. The effects are driven by firms in the manufacturing sector. Our results highlight the importance of the bank lending channel to stimulate employment in the short term, especially for smaller firms. Further, our estimates suggest that the effect of credit on employment could be amplified with policies that promote a more competitive corporate loan market.

Although still incipient in economics and finance, compositional data analysis (in which relative information is more important than absolute values are) has become more relevant in statistical analysis in recent years. This article constructs a concentration index for financial/banking systems via compositional analysis to establish the potential existence of “too big to fail” financial entities. The intention is to provide an early warning tool for regulators about this type of institution, so they can define thresholds and measures depending on their risk appetite and the systems’ specificities. The index has been applied to the Colombian banking system and assessed over time with a forecast to determine whether the system is becoming more concentrated. Results found that the concentration index has been decreasing in recent years and the model predicts this trend will continue. Regarding the methodology used, compositional models were shown to be more stable and to lead to better prediction of the index compared to the classical multivariate methodologies.

This paper analyzes the historical evidence of the gender gap in employment and wages in Mexico. We construct consistent time series from 1988:Q1 to 2019:Q4 using employment surveys, and estimate a model of labor participation in the formal market and wages for each gender and quarter, correcting selection biases. Based on these results, we implement a Blinder–Oaxaca (1973) and Mulligan-Rubinstein (2008) decomposition to estimate the gender gap in wages. Our results suggest the returns to schooling for both genders have decreased in the last two decades, showing a gap of almost 2% in favor of women. The gender wage gap fluctuates around 29.6% once self-selection bias is corrected. The prevalence of differences in expected wages between genders exists due to the "selection bias" and "residual" effects. This work's main limitation is that it focuses only on formal urban employment in 16 metropolitan areas; however, this approach makes it possible to identify long-term trends and structural changes in this market, expanding the evidence of the gender gap in the Mexican economic history.

Resumen

El objetivo de este artículo es analizar la evidencia histórica de la brecha de género en el empleo y los salarios en México. Para ello, construimos series de tiempo consistentes desde 1988:Q1 hasta 2019:Q4 utilizando encuestas de empleo en México, y estimamos en cada trimestre un modelo de participación laboral y salarios para cada segmento de género del mercado formal, corrigiendo el sesgo de selección correspondiente. A partir de estos resultados, implementamos una descomposición Blinder-Oaxaca (1973) y Mulligan-Rubinstein (2008) para estimar la brecha salarial de género. Nuestros resultados sugieren que los rendimientos de la escolaridad para ambos géneros han disminuido en las dos últimas décadas, mostrando una brecha de casi 2% a favor de las mujeres. La diferencia salarial entre ambos sexos fluctúa en torno al 29.6% una vez corregido el sesgo de autoselección. La prevalencia de las diferencias en los salarios esperados entre géneros existe debido a los efectos de "sesgo de selección" y "residual". Una limitación de este trabajo es que sólo se centra en el empleo urbano formal en 16 áreas metropolitanas; sin embargo, este enfoque permite identificar las tendencias de largo plazo y los cambios estructurales en este mercado, expandiendo la evidencia de la brecha de género en la historia económica mexicana.

We evaluate the dynamics of a small and open economy under simple rules for alternative monetary-policy instruments, in a model with imperfectly anchored expectations. The inflation-targeting consensus indicates that interest-rate rules are preferred, instead of using either a monetary aggregate or the exchange rate as the main instrument; with arguments usually presented under rational expectations and full credibility. In contrast, we assume agents use econometric models to form inflation expectations, capturing limited credibility. We compare the dynamics after a shock to external-borrowing costs (arguably one of the most important sources of fluctuations in emerging countries) under three policy rules: a Taylor-type rule for the interest rate, a constant-growth-rate rule for monetary aggregates, and a fixed exchange rate. The analysis identifies relevant trade-offs in choosing among alternative instruments, highlighting specially the role of exchange-rate volatility in shaping medium- and long-term inflation forecasts, and its consequences for policy design.

We develop an unsupervised methodology to group payments and identify possible anomalies. With our methodology, we identify clusters based on a set of network features, using transactional (unlabeled) information from a systemically important payment system of El Salvador. We first preprocess network features, such as degree and strength, through a principal components analysis we reduce the dimensionality of the newly defined data, then we place the main variables into clustering algorithms (k-means and DBSCAN) to analyze anomalous payments. We then analyze, these clusters using random forest to obtain the main network feature. Our results suggest that the proposed methodology works very well to detect anomalous payments, and it is very important to study the case of El Salvador, because of the recent restructuring of the Massive Payment System in El Salvador (promoted by the Transfer365 project), because the authorities want to increase financial inclusion. This change will make the SPM available to the public, to diversify services and incorporate more participants because, historically, it has operated with only three active participants. We expected that Transfer365 will interconnect the LBTR participants' systems with their banking core, the systems of the Ministry of Finance, and other authorized participants to channel large payment flows. Then, identifying possible anomalies through methodology will enhance risk monitoring and management by payment systems overseers.

This paper uses a rich weekly price database from the largest supermarket in Uruguay to analyze the relationship among prices, micro-level sales, and business cycle conditions. On average, 7% of products were on sale each month, and we show a positive and statistically significant but small relationship between sales and unemployment at the aggregate level, controlling for product and time effects. For each product category, there is a high and positive statistically significant association for these variables. Also, for some categories like food products, alcoholic drinks, beverages, and fruits and vegetables, we found a large, negative, and statistically significant relationship between the probability of being on sale and employment. The mechanism we tested is the following: As the economy worsens and unemployment rises (and/or employment falls), the supermarket uses sales to adjust prices while keeping reference prices fixed. Our results indicate that sales do not alleviate much of the price rigidity in economic recessions.

We also studied sales behavior through a principal component analysis in the time domain. This analysis revealed that the first two principal components explained more than half of each sector’s variance in price dynamics. These components are significantly correlated with variations in unemployment and employment. Additionally, we found that movement in the principal components across sectors systematically Granger-cause employment changes.

In this paper, we investigate the growing prominence of credit in the systemic banking crisis prediction literature. Through the application of the signal extraction model and multivariate probit panel regression, we evaluate the performance of the absolute change in credit-to-GDP ratio as an early warning system indicator of systemic banking crises. The findings reveal that the accelerated financialisation of economies turns the excess supply of credit into generating conditions that increase the likelihood of a systemic banking crisis. The findings also indicate that even with persistently low and stable inflation, systemic risk could gradually accumulate through an excessive supply of credit.