International Monetary Fund. Asia and Pacific Dept
The coronavirus disease (COVID-19) pandemic is still unfolding around the globe. In Asia, as elsewhere, the virus has ebbed in some countries but surged in others. The global economy is beginning to recover after a sharp contraction in the second quarter of 2020, as nationwide lockdowns are lifted and replaced with more targeted containment measures.
Luis Franjo, Nathalie Pouokam, and Francesco Turino
In this paper we build a model of occupational choice with informal production and progressive income taxation. We calibrate the model to the Brazilian economy to evaluate the impact of removing financial frictions on informality. We find that financial deepening leads to a drop in the size of the informal sector (from 37 percent to 22 percent of official GDP), to an increase in measured TFP (by 4 percent), to an increase in official GDP (by 27 percent), to a decrease in tax evasion (by 17 percent) and to an increase in fiscal revenues (by 15 percent). When assessing the response of this policy at different levels of financial development, we find a non-linear relationship between the credit-to-GDP ratio on the one hand, and either the size of the informal economy, or GDP per capita on the other hand. We test these features with cross-country data and find evidence in favor of both types of non-linearity. We also investigate changes in the income tax progressitivity as an alternative policy and find it to be more effective in countries with a medium to high level of financial markets development.
Jin-Kyu Jung, Manasa Patnam, and Anna Ter-Martirosyan
Forecasting macroeconomic variables is key to developing a view on a country's economic outlook.
Most traditional forecasting models rely on fitting data to a pre-specified relationship between input
and output variables, thereby assuming a specific functional and stochastic process underlying that
process. We pursue a new approach to forecasting by employing a number of machine learning
algorithms, a method that is data driven, and imposing limited restrictions on the nature of the true
relationship between input and output variables. We apply the Elastic Net, SuperLearner, and
Recurring Neural Network algorithms on macro data of seven, broadly representative, advanced and
emerging economies and find that these algorithms can outperform traditional statistical models,
thereby offering a relevant addition to the field of economic forecasting.
This report discusses fiscal trends in policies aimed at reducing fiscal vulnerabilities and boosting medium-term growth, recent fiscal developments and the fiscal outlook in advanced economies, emerging markets, and low-income developing countries; recent trends in government debt and analysis of changes in fiscal balances, revenue, and spending; potential fiscal risks; and growth from the fiscal policies. It also describes how digitalization can help governments improve implementation of current policy and widen the range of policy options, and opportunities and risks for fiscal policy, including improvements in policy implementation, the design of future policy, and how digitalization can create opportunities for fraud and increase government vulnerabilities.
Macroeconomic analysis in Lebanon presents a distinct challenge. For example, long
delays in the publication of GDP data mean that our analysis often relies on proxy
variables, and resembles an extended version of the “nowcasting” challenge familiar to
many central banks. Addressing this problem—and mindful of the pitfalls of extracting
information from a large number of correlated proxies—we explore some recent
techniques from the machine learning literature. We focus on two popular techniques
(Elastic Net regression and Random Forests) and provide an estimation procedure that is
intuitively familiar and well suited to the challenging features of Lebanon’s data.
I study whether firms' reliance on intangible assets is an important determinant of financing constraints. I construct new measures of firm-level physical and intangible assets using accounting information on U.S. public firms. I find that firms with a higher share of intangible assets in total assets start smaller, grow faster, and have higher Tobin’s q. Asset tangibility predicts firm dynamics and Tobin’s q up to 30 years but has diminishing predicative power. I develop a model of endogenous financial constraints in which firm size and value are limited by the enforceability of financial contracts. Asset tangibility matters because physical and intangible assets differ in their residual value when the contract is repudiated. This mechanism is qualitatively important to explain stylized facts of firm dynamics and Tobin’s q.
This paper proposes a tractable Sudden Stop model to explain the main patterns in firm level data in a sample of Southeast Asian firms during the Asian crisis. The model, which features trend shocks and financial frictions, is able to generate the main patterns observed in the sample during and following the Asian crisis, including the ensuing credit-less recovery, which are also patterns broadly shared by most Sudden Stop episodes as documented in Calvo et al. (2006). The model also proposes a novel explanation as to why small firms experience steeper declines than their larger peers as documented in this paper. This size effect is generated under the assumption that small firms are growth firms, to which there is support in the data. Trend shocks when combined with financial frictions in this model also generate strong leverage effects in line with what is observed in the sample, and with other observations from the literature.
This paper demonstrates that the Dutch disease need not materialize in low-income countries that can draw on their idle productive capacity to satisfy the aid-induced increased demand. Diagnoses on, and prognoses for, the Dutch disease should take into account country-specific circumstances to avoid ill-advised policies. The paper emphasizes that using public resources inefficiently can be more painful than real exchange rate appreciations, which may not necessarily embody the Dutch disease.