How much fiscal space do Latin American countries have to increase their tax burdens in the long term? This paper provides an answer through Laffer curves estimates for taxes on labor, capital, and consumption for the six largest emerging economies of the region: Argentina, Brazil, Chile, Colombia, Mexico, and Peru. Estimates are made using a neoclassical growth model with second-generation human capital and employing data from the national accounts system for the period from 1994 to 2017. Our findings allow us to compare the recent effective tax rates on factor returns against those which would maximize the government's revenues, and therefore to derive the potential tax-related fiscal space. Results suggest that joint fiscal space on labor and capital taxes would reach 6.5% of GDP for the region, on average, and that there are important differences among the countries.
{"title":"How do the Tax Burden and the Fiscal Space in Latin America look like? Evidence through Laffer Curves","authors":"Ignacio Lozano-Espitia, Fernando Arias-Rodríguez","doi":"10.32468/be.1117","DOIUrl":"https://doi.org/10.32468/be.1117","url":null,"abstract":"How much fiscal space do Latin American countries have to increase their tax burdens in the long term? This paper provides an answer through Laffer curves estimates for taxes on labor, capital, and consumption for the six largest emerging economies of the region: Argentina, Brazil, Chile, Colombia, Mexico, and Peru. Estimates are made using a neoclassical growth model with second-generation human capital and employing data from the national accounts system for the period from 1994 to 2017. Our findings allow us to compare the recent effective tax rates on factor returns against those which would maximize the government's revenues, and therefore to derive the potential tax-related fiscal space. Results suggest that joint fiscal space on labor and capital taxes would reach 6.5% of GDP for the region, on average, and that there are important differences among the countries.","PeriodicalId":43785,"journal":{"name":"Latin American Economic Review","volume":"63 1","pages":""},"PeriodicalIF":0.5,"publicationDate":"2020-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80643775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper quantifies and assesses the impact of an adverse loan supply (LS) shock on Peru's main macroeconomic aggregates using a Bayesian vector autoregressive (BVAR) model in combination with an identification scheme with sign restrictions. The main results indicate that an adverse LS shock: (i) reduces credit and real GDP growth by 372 and 75 basis points in the impact period, respectively; (ii) explains 11.2% of real GDP growth variability on average over the following 20 quarters; and (iii) explained a 180-basis point fall in real GDP growth on average during 2009Q1-2010Q1 in the wake of the Global Financial Crisis (GFC). Additionally, the sensitivity analysis shows that the results are robust to alternative identification schemes with sign restrictions; and that an adverse LS shock has a greater impact on non-primary real GDP growth.
{"title":"Macroeconomic Effects of Loan Supply Shocks: Empirical Evidence for Peru","authors":"Jefferson Martínez, G. Rodríguez","doi":"10.47872/laer-2021-30-5","DOIUrl":"https://doi.org/10.47872/laer-2021-30-5","url":null,"abstract":"This paper quantifies and assesses the impact of an adverse loan supply (LS) shock on Peru's main macroeconomic aggregates using a Bayesian vector autoregressive (BVAR) model in combination with an identification scheme with sign restrictions. The main results indicate that an adverse LS shock: (i) reduces credit and real GDP growth by 372 and 75 basis points in the impact period, respectively; (ii) explains 11.2% of real GDP growth variability on average over the following 20 quarters; and (iii) explained a 180-basis point fall in real GDP growth on average during 2009Q1-2010Q1 in the wake of the Global Financial Crisis (GFC). Additionally, the sensitivity analysis shows that the results are robust to alternative identification schemes with sign restrictions; and that an adverse LS shock has a greater impact on non-primary real GDP growth.","PeriodicalId":43785,"journal":{"name":"Latin American Economic Review","volume":"17 1","pages":""},"PeriodicalIF":0.5,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82969126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.47872/laer-2020-29-3s
Raul Jimenez Mori, Ariel Yépez-García
The paper investigates the determinants of household energy spending and energy budget shares, with a focus on understanding their non-linear relationship with income, and the presence of economies of scale. The analysis is based on a unique, harmonized collection of official household surveys from 13 Latin American countries. This dataset allows distinguishing between expenditures on electricity, domestic gas, and fuel for private transportation, providing a comprehensive distributional view of the energy spending profile of the residential sector. The estimated empirical Engel curves behave similarly; however, the derived income elasticities show marked distinctions by fuel, and their actual values depend on the households’ relative position over the income distribution. For electricity, the elasticity tends to increase in income but stabilize at the wealthiest segments. For gas and transport fuel, it decreases under different income paths. In this dataset, the examination returns income elasticities on the (0,1) interval, suggesting that energy commodities are necessity goods. However, the distribution of aggregate energy expenditure needs to be considered. Specifically, there is a great concentration among the richer groups, particularly for transport fuels, where the top quintile gathers more than half of the aggregate spending. The results also indicate economies of scale ––for electricity and domestic gas–– with respect to family-age composition, and to a lesser extent with respect to dwelling size. In the case of electricity, these economies are more pronounced for richer households. These results join the previous literature in emphasizing the relevance of accounting for household demographic and socioeconomic trends for energy management.
{"title":"Understanding the Drivers of Household Energy Spending: Micro Evidence for Latin\u0000America","authors":"Raul Jimenez Mori, Ariel Yépez-García","doi":"10.47872/laer-2020-29-3s","DOIUrl":"https://doi.org/10.47872/laer-2020-29-3s","url":null,"abstract":"The paper investigates the determinants of household energy spending and energy budget shares, with a focus on understanding their non-linear relationship with income, and the presence of economies of scale. The analysis is based on a unique, harmonized collection of official household surveys from 13 Latin American countries. This dataset allows distinguishing between expenditures on electricity, domestic gas, and fuel for private transportation, providing a comprehensive distributional view of the energy spending profile of the residential sector. The estimated empirical Engel curves behave similarly; however, the derived income elasticities show marked distinctions by fuel, and their actual values depend on the households’ relative position over the income distribution. For electricity, the elasticity tends to increase in income but stabilize at the wealthiest segments. For gas and transport fuel, it decreases under different income paths. In this dataset, the examination returns income elasticities on the (0,1) interval, suggesting that energy commodities are necessity goods. However, the distribution of aggregate energy expenditure needs to be considered. Specifically, there is a great concentration among the richer groups, particularly for transport fuels, where the top quintile gathers more than half of the aggregate spending. The results also indicate economies of scale ––for electricity and domestic gas–– with respect to family-age composition, and to a lesser extent with respect to dwelling size. In the case of electricity, these economies are more pronounced for richer households. These results join the previous literature in emphasizing the relevance of accounting for household demographic and socioeconomic trends for energy management.","PeriodicalId":43785,"journal":{"name":"Latin American Economic Review","volume":"3 1","pages":""},"PeriodicalIF":0.5,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79097886","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}