Informal sector, productivity, and tax collection

The informal sector is a prominent characteristic of many developing countries. Most of the literature has focused on understanding the determinants of informality. The connection between the informal sector and economic development is, nonetheless, relatively less understood. One of the most important determinants of informality is the tax enforcement quality of a country which, some authors argue, additionally distorts firms' decisions and creates inefficiency. In this paper, I assess the quantitative importance of the effects of incomplete tax enforcement on aggregate output and productivity. I use a dynamic general equilibrium framework to study effects that have received little attention in the literature. I calibrate the model using data for Mexico, an economy where 31% of the employees work in informal establishments. I then investigate the effects of improving enforcement. My main finding is that under complete enforcement, Mexico's labor productivity and output would be 17% higher.Informal Sector, Productivity, tax enforcement, TFP, Heterogeneous plants

Informal sector, productivity, and tax collection

The informal sector is a prominent characteristic of many developing countries. Most of the literature has focused on understanding the determinants of informality. The connection between the informal sector and economic development is, nonetheless, relatively less understood. One of the most important determinants of informality is the tax enforcement quality of a country which, some authors argue, additionally distorts firms' decisions and creates inefficiency. In this paper, I assess the quantitative importance of the effects of incomplete tax enforcement on aggregate output and productivity. I use a dynamic general equilibrium framework to study effects that have received little attention in the literature. I calibrate the model using data for Mexico, an economy where 31% of the employees work in informal establishments. I then investigate the effects of improving enforcement. My main finding is that under complete enforcement, Mexico's labor productivity and output would be 17% higher

Taxes, Transfers and the Distribution of Employment in Mexico

The informal sector accounts for a substantial fraction of employed population in Mexico and other Latin American countries. In this paper we study the interaction between the tax and transfers system and the size and composition of informal sector. To do that we build a search model that can be calibrated to the Mexican data. Our model features two employment statuses: employed and unemployed; and two sectors: formal and informal. We estimate our model to data from Encuesta Nacional de Ocupaci ́on y empleo (ENOE) by simulated GMM. Then we perform three different policy analyses: changes in the distribution of the transfers between formal and informal sector workers, changes in the size of the transfer system, and changes in the progressivity of taxes and transfers (pending). Our model is able to capture key features of Mexican labor markets, such as the distribution of the labor force across sectors and the distribution of accepted wage offers. Dividing transfers equally between formal and informal sector workers increases the size of the informal sector by 5 percentage points, it also increases average wages in the formal sector by 6% whereas wages in the informal sector fall by 4%. When we double the size of transfers, the size of informal sector falls by 5 percentage points. However, it has a big effect on the distribution of accepted wage offers: average wages increase by 10% in the formal sector and they raise by 16% in the informal sector

Taxes, Transfers and the Distribution of Employment in Mexico

The informal sector accounts for a substantial fraction of employed population in Mexico and other Latin American countries. In this paper we study the interaction between the tax and transfers system and the size and composition of informal sector. To do that we build a search model that can be calibrated to the Mexican data. Our model features two employment statuses: employed and unemployed; and two sectors: formal and informal. We estimate our model to data from Encuesta Nacional de Ocupaci ́on y empleo (ENOE) by simulated GMM. Then we perform three different policy analyses: changes in the distribution of the transfers between formal and informal sector workers, changes in the size of the transfer system, and changes in the progressivity of taxes and transfers (pending). Our model is able to capture key features of Mexican labor markets, such as the distribution of the labor force across sectors and the distribution of accepted wage offers. Dividing transfers equally between formal and informal sector workers increases the size of the informal sector by 5 percentage points, it also increases average wages in the formal sector by 6% whereas wages in the informal sector fall by 4%. When we double the size of transfers, the size of informal sector falls by 5 percentage points. However, it has a big effect on the distribution of accepted wage offers: average wages increase by 10% in the formal sector and they raise by 16% in the informal sector

In COVID-19 health messaging, loss framing increases anxiety with little-to-no concomitant benefits: Experimental evidence from 84 countries

The COVID-19 pandemic (and its aftermath) highlights a critical need to communicate health information effectively to the global public. Given that subtle differences in information framing can have meaningful effects on behavior, behavioral science research highlights a pressing question: Is it more effective to frame COVID-19 health messages in terms of potential losses (e.g., “If you do not practice these steps, you can endanger yourself and others”) or potential gains (e.g., “If you practice these steps, you can protect yourself and others”)? Collecting data in 48 languages from 15,929 participants in 84 countries, we experimentally tested the effects of message framing on COVID-19-related judgments, intentions, and feelings. Loss- (vs. gain-) framed messages increased self-reported anxiety among participants cross-nationally with little-to-no impact on policy attitudes, behavioral intentions, or information seeking relevant to pandemic risks. These results were consistent across 84 countries, three variations of the message framing wording, and 560 data processing and analytic choices. Thus, results provide an empirical answer to a global communication question and highlight the emotional toll of loss-framed messages. Critically, this work demonstrates the importance of considering unintended affective consequences when evaluating nudge-style interventions