{"title":"Evaluating core inflation measures: A statistical inference approach","authors":"Juan Carlos Castañeda, Rodrigo Chang","doi":"10.1016/j.latcb.2023.100099","DOIUrl":"https://doi.org/10.1016/j.latcb.2023.100099","url":null,"abstract":"<div><p>We propose a framework for consistently evaluating core inflation measures via a straightforward application of sound statistical inference principles. Under this framework, inflation measures (both headline and core) are regarded as estimators tracking the economy’s true, unobserved inflation rate. We depart from the arbitrary convention in the literature of approximating true (or trend) inflation as some moving average of the observed headline inflation. Instead, we regard trend inflation as the unobserved inflation rate that corresponds to the whole population of consumer price changes while the observed inflation measures are estimators of trend inflation based on particular samples of consumer price changes. Hence, the evaluation of inflation measures is rigorously derived from the sampling distribution properties of the corresponding estimators, in contrast to the use of ad hoc criteria for evaluating core inflation measures, prevalent both in the academic literature and in most central banks’ practices. We implement our evaluation approach for the Guatemalan Consumer Price Index (CPI) data by applying a computational bootstrapping technique. Finally, we showcase the evaluation results for the Guatemalan data regarding the performance of some widely used core inflation measures.</p></div>","PeriodicalId":100867,"journal":{"name":"Latin American Journal of Central Banking","volume":"4 4","pages":"Article 100099"},"PeriodicalIF":0.0,"publicationDate":"2023-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50204478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ali Nassiri Aghdam, Shahin Behdarvand, Mohammad Ghasemi Sheshdeh
{"title":"The effect of credit composition on entrepreneurship","authors":"Ali Nassiri Aghdam, Shahin Behdarvand, Mohammad Ghasemi Sheshdeh","doi":"10.1016/j.latcb.2023.100103","DOIUrl":"https://doi.org/10.1016/j.latcb.2023.100103","url":null,"abstract":"<div><p>In this study, we aim to assess the relevance of credit composition to entrepreneurship empirically in light of the Schumpeterian perspective. The results of such an analysis can imply whether central banks should continue with the so-called neutrality principle or undertake an active credit policy. We employ a panel data model to quantify the effect of credit composition on entrepreneurship in 54 high- and middle-income economies from 2001 to 2016. To capture credit composition, we disaggregate total credit as credit to non-financial and financial businesses as well as credit to households and mortgages, and we hypothesize that the larger share of credit for non-financial businesses and households would be associated with greater entrepreneurship. The results indicate that credit composition is important for both high- and middle-income economies, but the effective composition of credit is different in the two sub-samples, which is why the effectiveness of credit allocation should not be taken for granted and active remedies are required. This paper corroborates the Schumpeterian view on the ties between credit allocation and entrepreneurship in both high- and middle-income economies.</p></div>","PeriodicalId":100867,"journal":{"name":"Latin American Journal of Central Banking","volume":"4 4","pages":"Article 100103"},"PeriodicalIF":0.0,"publicationDate":"2023-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50204477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Elías Albagli , Alejandra Chovar , Emiliano Luttini , Carlos Madeira , Alberto Naudon , Matias Tapia
{"title":"Labor market flows: Evidence for Chile using microdata from administrative tax records","authors":"Elías Albagli , Alejandra Chovar , Emiliano Luttini , Carlos Madeira , Alberto Naudon , Matias Tapia","doi":"10.1016/j.latcb.2023.100102","DOIUrl":"https://doi.org/10.1016/j.latcb.2023.100102","url":null,"abstract":"<div><p>We compute and characterize several labor flow measures using administrative tax records for all formal Chilean firms and employees. Our results show that labor mobility in Chile is significant by international standards, with the reallocation rate averaging 37% over the last decade, the highest value among the 25 OECD countries with comparable data. The magnitude of labor reallocation is highly heterogeneous among firms and industries, highest in Agriculture and Construction. Job reallocation is also high for smaller companies, primarily due to high firm creation and destruction rates, and for firms that pay lower wages. Finally, there is a significant procyclical behavior of workers’ entry rate and, in smaller magnitude, a countercyclical reaction of the exit rate, consistent with international evidence that shows job creation as the main adjustment mechanism over the business cycle.</p></div>","PeriodicalId":100867,"journal":{"name":"Latin American Journal of Central Banking","volume":"4 4","pages":"Article 100102"},"PeriodicalIF":0.0,"publicationDate":"2023-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50204476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Constanza Martínez-Ventura , Ricardo Mariño-Martínez, Javier Miguélez-Márquez
{"title":"Redundancy of Centrality Measures in Financial Market Infrastructures","authors":"Constanza Martínez-Ventura , Ricardo Mariño-Martínez, Javier Miguélez-Márquez","doi":"10.1016/j.latcb.2023.100098","DOIUrl":"https://doi.org/10.1016/j.latcb.2023.100098","url":null,"abstract":"<div><p>The concept of centrality is widely used to monitor systems with a network structure because it allows identifying their most influential participants. This monitoring task can be difficult if the number of system participants is considerably large or if the wide variety of centrality measures currently available produce non-coincident (or mixed) signals. This document uses robust principal component analysis to evaluate a set of centrality measures calculated for the financial institutions that participate in Colombia's four financial market infrastructures. The results obtained are used to construct general indices of centrality, using the most robust measures of centrality as inputs and leaving aside those considered redundant.</p></div>","PeriodicalId":100867,"journal":{"name":"Latin American Journal of Central Banking","volume":"4 4","pages":"Article 100098"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50204441","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Exposures to climate change's physical risks in Chile","authors":"Magdalena Cortina , Carlos Madeira","doi":"10.1016/j.latcb.2023.100090","DOIUrl":"https://doi.org/10.1016/j.latcb.2023.100090","url":null,"abstract":"<div><p>We estimate real estate’s exposure in Chile to five weather risks, including labor productivity loss due to heat, fires, floods, drought coastal deterioration as measured by the Chilean Climatic Risk Atlas (ARCLIM) and Climate Impact Explorer (CIE) sources. According to our joint ARCLIM-CIE indicator, we measure risk exposure for the appraisal value of all properties of 39% for Chile and 51%, 36%, 36% and 27% for the Central, North, Metropolitan and South macrozones, respectively. Flooding is the greatest risk for Chile, followed by drought. We find that the CIE source underestimates the climate exposures in Chile relative to the ARCLIM measures, particularly for the flooding and drought risks.</p></div>","PeriodicalId":100867,"journal":{"name":"Latin American Journal of Central Banking","volume":"4 2","pages":"Article 100090"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49881162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Machine learning methods for inflation forecasting in Brazil: New contenders versus classical models","authors":"Gustavo Silva Araujo , Wagner Piazza Gaglianone","doi":"10.1016/j.latcb.2023.100087","DOIUrl":"https://doi.org/10.1016/j.latcb.2023.100087","url":null,"abstract":"<div><p>In this paper, we explore machine learning (ML) methods to improve inflation forecasting in Brazil. An extensive out-of-sample forecasting exercise is designed with multiple horizons, a large database of 501 series, and 50 forecasting methods, including new ML techniques proposed here, traditional econometric models and forecast combination methods. We also provide tools to identify the key variables to predict inflation, thus helping to open the ML black box. Despite the evidence of no universal best model, the results indicate that ML methods can, in numerous cases, outperform traditional econometric models in terms of mean-squared error. Moreover, the results indicate the existence of nonlinearities in the inflation dynamics, which are relevant to forecasting inflation. The set of top forecasts often includes forecast combinations, tree-based methods (such as random forest and xgboost), breakeven inflation, and survey-based expectations. Altogether, these findings offer a valuable contribution to macroeconomic forecasting, especially, focused on Brazilian inflation.</p></div>","PeriodicalId":100867,"journal":{"name":"Latin American Journal of Central Banking","volume":"4 2","pages":"Article 100087"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49881158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Exchange rate volatility and the effectiveness of FX interventions: The case of Chile","authors":"Alejandro Jara, Marco Piña","doi":"10.1016/j.latcb.2023.100086","DOIUrl":"https://doi.org/10.1016/j.latcb.2023.100086","url":null,"abstract":"<div><p>In this paper, we study the effectiveness of FX interventions in Chile since adopting a fully flexible exchange rate regime in the late 1990s. In particular, we ask whether these interventions have dumped excess exchange rate volatility and reduced its probability of being in a high volatility state. To do so, we rely on a high-frequency GARCH(1,1) volatility model with Markov-Switching regimes and evaluate the effectiveness of FX interventions within a local projection setting. We show that FX interventions in Chile tend to occur during high exchange rate volatility periods, which correlate with domestic and foreign financial factors. Moreover, we show that the FX intervention that started by the end of 2019–the latest intervention included in our study–effectively reduced the exchange rate volatility and the probability of being at a high volatility state.</p></div>","PeriodicalId":100867,"journal":{"name":"Latin American Journal of Central Banking","volume":"4 2","pages":"Article 100086"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49881159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The impact of monetary policy on a labor market with heterogeneous workers: The case of Chile","authors":"Carlos Madeira , Leonardo Salazar","doi":"10.1016/j.latcb.2023.100092","DOIUrl":"https://doi.org/10.1016/j.latcb.2023.100092","url":null,"abstract":"<div><p>We use a factor-augmented vector autoregressive (FAVAR) model to analyze the effect of a contractionary monetary policy shock on macroeconomic aggregates and labor market indicators for different demographic groups in Chile classified by industry, age, and income quintile. Inflation is negatively correlated with unemployment across groups. The model shows that most groups’ job-separation rate and wage volatility increase after an interest rate rise. The response of the job-finding rate is mixed, decreasing in some groups and rising in others after an interest rate shock. The labor market in the primary sector is the least sensitive to monetary shocks.</p></div>","PeriodicalId":100867,"journal":{"name":"Latin American Journal of Central Banking","volume":"4 2","pages":"Article 100092"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49881160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Elizabeth Bucacos , Patricia Carballo , Miguel Mello , Jorge Ponce
{"title":"Policy responses to COVID-19 in Uruguay","authors":"Elizabeth Bucacos , Patricia Carballo , Miguel Mello , Jorge Ponce","doi":"10.1016/j.latcb.2023.100085","DOIUrl":"https://doi.org/10.1016/j.latcb.2023.100085","url":null,"abstract":"<div><p>COVID-19 caused an overwhelming wave with large social and economic consequences and huge policy challenges. We provide an evaluation of the impact of the social, economic, and financial policy measures undertaken to ameliorate its negative consequences in Uruguay. Overall, we find that the policy response had a significant effect on mitigating the negative impact of the pandemic in the country. We also discuss policy implications.</p></div>","PeriodicalId":100867,"journal":{"name":"Latin American Journal of Central Banking","volume":"4 2","pages":"Article 100085"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49881802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Untangling crises: GFC and COVID-19 through the lens of a DSGE model","authors":"Rogelio De La Peña , Ignacio García","doi":"10.1016/j.latcb.2023.100091","DOIUrl":"https://doi.org/10.1016/j.latcb.2023.100091","url":null,"abstract":"<div><p>In this paper, we aim to compare the anatomy of the impact of the COVID-19 outbreak and the Great Financial Crisis (GFC) in the context of an emerging market economy. To this end, we develop a small open economy DSGE model with the Bernanke-Gertler-Gilchrist financial accelerator that features financial frictions and monopolistic competition. Then, we estimate this model to explore and compare both crises in the Mexican business cycle. The decomposition obtained with the model shows that: (i) the financial shocks were the main source of contraction of the output gap (around 49.0%) in the GFC; (ii) the dynamic of the GDP had been severely affected by the demand shock (around 45.1%), the financial shocks (32.2%), and the productivity shock (22.3%) in the COVID-19 pandemic. The results suggest that the main forces of the recent contraction in economic activity in Mexico were larger in absolute terms and more diverse than those observed during the GFC. This analysis illustrates the differences between the two great crises and it evaluates the policy response to each.</p></div>","PeriodicalId":100867,"journal":{"name":"Latin American Journal of Central Banking","volume":"4 2","pages":"Article 100091"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49881161","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}