EconomiA最新文献

The COVID-19 pandemic has already made a significant impact on various sectors. No country was fully prepared to face this global pandemic, and Indonesia is no exception. For Indonesia, this pandemic shook not only the public health service system but also the economy. This study makes projections related to the impact of this pandemic on the Indonesian economy by utilising a computable general equilibrium (CGE) model. Additionally, we calculate the land needed to cover the demand for agricultural products, as well as the level to which emissions can be reduced. Our simulation shows that, along with every shock caused by COVID-19 to national supply and demand, Indonesia will be experiencing economic stagnation by 2021, with the gross domestic product (GDP) level 4–8% lower than the business as usual (BAU) level during the pandemic (2020–2021). The two sectors that will be hit hardest are the transportation and tourism sectors, making up a GDP loss ranging from 30% to 50%. During this stagnation, the agricultural sector is a potential sector for accommodating workers who have been laid off. The model also predicts that there will be a temporary land-use change that the farmers will prefer to use their land for food and horticultural commodities. As for emissions, our calculations show that the potential for emission reductions will be up to 8% by 2021, compared to the BAU level. However, the source of this emission reduction is not positive as it comes from the restriction of economic activity, and the growth in emissions from the industrial and waste sectors are still increasing rapidly, even during the pandemic. Thus, it is feared that there will be a very high spike in emissions when the pandemic ends, making the situation more challenging for Indonesia to achieve its emission mitigation targets. Furthermore, once the government introduces fiscal incentives to support the economy during the pandemic, the economic condition will be improved, although still not fully recovered. The model predicts that the government fiscal incentives may help to improve the GDP by around 1–3%, compared to when no incentive is introduced.

We applied the SIR-macro model proposed by Eichenbaum et al. (2020) in its complete version to comparatively study the interaction between economic decisions and COVID-19 epidemics in five different Brazilian states: São Paulo (SP), Amazonas (AM), Ceará (CE), Rio de Janeiro (RJ), and Pernambuco (PE). Our goal was to analyze qualitatively how the main intrinsic differences of each of these states could affect the epidemic dynamics and its consequences. We computed and compared the model for each of the states, both in competitive equilibrium and under optimal containment policy adoption, and analyzed the implications of optimal policy adoption. We concluded that the intrinsic characteristics of the five different states could imply relevant differences in the general dynamics of the epidemic, in the optimal containment policies, in the effect of the adoption of these policies, and the severity of the economic recessions. One year after the original ex-ante calibration, we evaluated the death toll and economic recession predicted by the model comparing it against real data. The model predictions showed to be qualitatively sufficient to anticipate the size of the pandemic risk that later materialized in Brazil.

Concern over the high rate of contagion of COVID-19 has prompted world authorities to use the strategy of isolation and social confinement as the main non-pharmacological weapon against the disease that has rapidly killed millions of people worldwide. However, there is evidence that the denialist rhetoric of the Brazilian President has negatively influenced people's behavior in relation to obedience to confinement and social isolation measures. The aim of this study is to analyze the correlation between the Brazilian President’s denialist rhetoric and the low adherence to social distancing measures and the subsequent increase of new coronavirus cases and deaths. Daily data on the level of contamination by COVID-19, social distancing and information from Brazilian states between the months of February and May 2020 were used. Taking into consideration the differences between the federal government of Brazil and state governors about the severity of the pandemic and the importance of social distancing, the article uses the Instrumented Difference-in-Differences approach, suggested by Duflo (2001), to obtain the causal impact of reduced social distancing, resulting from Presidential denialist rhetoric, in mitigating COVID-19 cases and deaths, taking into account the relationship between the president of the republic and the states as an instrument. The results suggest that the Brazilian average Social Isolation Index increased from 39.77% to 51% between February 1st and May 18th, 2020, the country would have had approximately 318,850.03 fewer cases of COVID-19, and more than 10.000 lives would have been saved.

Recent studies have shown that COVID-19 affects different population groups asymmetrically. This work uses data from the National Survey of Households—PNAD COVID-19/IBGE—to quantify the socioeconomic inequality in health during the first wave of COVID-19 infections in Brazil. We use the concentration curve, the concentration index, and a decomposition analysis to verify the factors that most influence the inequalities in the specified health variables. We find a positive concentration index for the incidence rate, indicating a greater concentration of diagnoses (number of tests) among groups with higher income levels. When considering symptoms similar to a COVID-19 infection, inequality practically disappears. Among people with higher income, a pre-existing disease has a more significant contribution to the concentration of COVID-19 in the presence of correlated symptoms than in its diagnosis. Tests of dominance support the findings. Moreover, the decomposition results show that if the inequalities were explained only by race (non-white) and place of living (North and Northeast), there would be a concentration of COVID-19 among the poorest.

How do changes in mobility impact crime? Using police precinct-level daily crime statistics and shootings data from the state of Rio de Janeiro, Brazil, we estimate that extortion, theft, and robberies decrease by at least 41.6% following COVID-19 mandated stay-at-home orders and changes in mobility in March 2020. Conversely, we find no change in violent crimes, despite fewer people being on the streets. To address the relationship between crime and mobility, we use cellphone data and split the precincts into subgroups by pre-Covid-19-related restrictions mobility quintiles. We estimate a similar average decrease in extortion regardless of a precinct’s previous activity level, but find that the decrease in theft and robberies is substantially higher for the more mobile precincts while it disappears for the least mobile precincts. Using daily cellphone mobility data aggregated at the police precinct level, we find that changes in mobility while the stay-at-home order is in place only have a meaningful effect on robberies, which increase in likelihood when a precinct’s mobility ranking is higher than the previous day. Together, these results suggest that the stay-at-home order and associated decline in mobility strongly affected extortion and property crimes while not interfering with the dynamics of violent crime. These findings support the hypothesis that violent and property crime follow different dynamics, particularly where there is a bigger impact of organized criminal groups.

Recent technological advancements and the digitization of most financial services have transformed the way by which individuals deal with their financial transactions. It has also affected the focus of financial institutions’ investments, as well as the sectors’ market dynamic, with the increasing number of start-ups and fintechs, which tends to lead to higher competition. Considering this scenario, our study explores the impacts that mobile and home banking had on bank fees charged to Brazilian consumers, from 2012 to 2019. As our theoretical framework, we use a network-city model, which is an evolution of the seminal linear and circular city models, while the econometric analysis is made using a time series model. Our findings show that bank fees were negatively affected by the digital banking platforms. In summary, the results indicate that the decrease on transport costs, caused by financial digitization and the widespread use of mobile and home banking, has reduced the price of bank fees to customers in the studied period.

The discriminatory component of the gender wage gap was found to be significant and to decrease over time by previous studies, most of them based on the Oaxaca-Blinder decomposition (OBD). Such evidence is disputable for being grounded on the assumption of full common support between men and women, which has been increasingly refuted by international literature. Seeking to fill this gap for the case of Brazil, the paper revisits household survey data from 1996 to 2015 with propensity score (PS) and nearest-neighbour (NN) matching techniques. As results, the discriminatory component was confirmed to be significant in all years and not to follow a systematic decaying trend across the years – the fall observed from 1996 to 2004 was offset in 65% by a subsequent increase. Gender discrimination was heterogeneous throughout occupational categories, being especially high in management positions. Estimates, albeit belonging to the range of previous studies, also challenged the gap closing trend suggested by these studies. Given ongoing recession and high informality, it is uncertain whether further progress towards gender wage equality in Brazil will emerge spontaneously from the private sector or whether specific policy is needed.

This paper theoretically and empirically investigates deindustrialization in a group of selected countries, from 1970 to 2017, viewing it as a process of varied and complex causes, sensitive to the degree of economic development. Supported by the theoretical framework on the centrality of the manufacturing industry for economic growth and the contextualization of recent trends in global industry, we seek to understand empirically the main determinants of deindustrialization through an econometric model of panel data analysis. The main objective, which is also the main contribution of this research, is to empirically investigate the determinants of deindustrialization considering the degree of development of the countries and with the understanding that the causes of this process can differ substantially. Our main results, in general, were aligned with the theoretical and empirical literature on the topic, while corroborating the hypothesis that certain variables are dependent on the level of economic development. In less developed countries, the exchange rate (depreciation) is correlated positively with the value added of the manufacturing sector, as is trade openness but in a negative way. In advanced countries, on the other hand, the relocation of physical production and the degree of financialization are highlighted as factors that negatively affect the manufacturing value added, while trade openness is positive. In view of these results, a more critical analysis on the causes and costs of deindustrialization is considered important, especially in developing countries.

This study uses data from the International Labor Organization’s 2013 school-to-work transition survey (SWTS) to measure intergenerational educational and occupational mobility in Brazil. The SWTS database contains information on youths from 15 to 29 years old as well as on family’s socioeconomic characteristics, both current and retrospective. This data set permits the measurement of intergenerational mobility. The results obtained show great intergenerational educational mobility, especially when parents had lower levels of education, and slightly less occupational mobility. To analyze the returns to education, earnings equations were estimated using the Heckman selection model. The education of youths and their parents had a great impact on youths’ earnings, mainly on females. Young women with higher education more than double their earnings compared to those without high school.

The paper investigates historical aspects of the formation of the scientific community of economists in Brazil, taking the current research effort about the economics of Covid-19 as a starting-point of the narrative. The transnational character of science in general and economics in particular is highlighted. The historical trajectory of economics in Brazil is compared to other sciences’, with attention to patronage and immigration. Economic debates surrounding the Spanish Flu outbreak in Brazil in 1918 are examined as an example of the working of the pre-scientific economic community in the country. Finally, some conclusions are drawn concerning the history of modern economic science in Brazil, with emphasis on the role of a couple of remarkably influential economists.