Saturday, January 22, 2022
From a paper by Tamás Kiss, Hoang Nguyen and Pär Österholm:
“In this paper, we have analysed the relevance of taking non-Gaussianity into account when empirically modelling Okun’s law in Australia, the euro area, the United Kingdom and the United States. Our results based on Bayesian VAR models with stochastic volatility suggest that heavier-than-Gaussian tails find support in some cases. Taking skewness into account is, however, less beneficial in this context considering our baseline sample. Our results confirm that it is important to account for heavy tails in the distribution of macroeconomic variables, an argument put forward by Fagiolo et al. (2008) and Ascari et al. (2015) among others.
It should be noted though that our results to some extent depend on whether data from the corona pandemic are included or not. We believe that including them might be problematic since they should probably be treated as outliers (see the discussion in Carriero et al., 2021). If they nevertheless are treated as regular observations, our analysis indicates that the evidence of non-Gaussianity strengthens. In addition, it can be noted that accounting for non-Gaussianity not only improves the model fit in several cases but it also captures the large swings in the variables without causing large swings in the stochastic volatility.
Apart from the modelling perspective, our analysis has also provided updated international empirical evidence concerning Okun’s law. We find that the dynamic relationship between the variables in all four economies is such that a shock to GDP growth has robustly negative effects on the change in the unemployment rate. This finding is robust to whether we include the period associated with the corona pandemic or not. It confirms Ball et al. (2017) and Ball et al. (2019) who argue that Okun’s law continues to be a robust relationship in empirical macroeconomics. This should be highly relevant information to the central banks of the economies studied here, suggesting that Okun’s law – which has been an important empirical relationship when modelling the economy continues to be useful regardless of modelling choices and time periods.”
From a paper by Tamás Kiss, Hoang Nguyen and Pär Österholm:
“In this paper, we have analysed the relevance of taking non-Gaussianity into account when empirically modelling Okun’s law in Australia, the euro area, the United Kingdom and the United States. Our results based on Bayesian VAR models with stochastic volatility suggest that heavier-than-Gaussian tails find support in some cases. Taking skewness into account is, however, less beneficial in this context considering our baseline sample.
Posted by at 9:50 AM
Labels: Macro Demystified
A recent working paper by A. Botta et al (2022) of the Levy Economics Institute analyzes factors that may have hindered productive development for over four decades prior to the COVID-19 pandemic.
Abstract: We investigate the role of (non-FDI) net capital inflows as a potential source of premature deindustrialization. We consider a sample of 36 developed and developing countries from 1980 to 2017, with major emphasis on the case of emerging and developing economies (EDE) in the context of increasing financial integration. We show that periods of abundant capital inflows may have caused the significant contraction of manufacturing share to employment and GDP, as well as the decrease of the economic complexity index. We also show that phenomena of “perverse” structural change are significantly more relevant in EDE countries than advanced ones. Based on such evidence, we conclude with some policy suggestions highlighting capital controls and external macroprudential measures taming international capital mobility as useful tools for promoting long-run productive development on top of strengthening (short-term) financial and macroeconomic stability.
A recent working paper by A. Botta et al (2022) of the Levy Economics Institute analyzes factors that may have hindered productive development for over four decades prior to the COVID-19 pandemic.
Abstract: We investigate the role of (non-FDI) net capital inflows as a potential source of premature deindustrialization. We consider a sample of 36 developed and developing countries from 1980 to 2017,
Posted by at 7:36 AM
Labels: Macro Demystified
Source: International Labor Organization
The report examines the impacts of the COVID-19 crisis on global and regional trends in employment, unemployment, and labor force participation, as well as on job quality, informal employment, and working poverty. It also offers an extensive analysis of trends in temporary employment both before and during the pandemic.
On the basis of the latest economic growth forecasts, the ILO is projecting that total hours worked globally in 2022 will remain almost 2 percent below their pre-pandemic level when adjusted for population growth, corresponding to a deficit of 52 million full-time equivalent jobs (assuming a 48-hour working week). Global unemployment is projected to stand at 207 million in 2022, surpassing its 2019 level by some 21 million. Region-wise, the European and Pacific regions are projected to come closest to that goal, whereas the outlook is the most negative for Latin America and the Caribbean and for SouthEast Asia.
The report also goes on to discuss ways for ensuring a sustainable and inclusive recovery. Action points highlighted in the adoption of the Global Call to Action for a Human Centred Recovery from the COVID-19 Crisis that is Inclusive, Sustainable and Resilient at the June 2021 ILO Conference are centered on the theme of addressing systemic and structural inequalities and other long-term social and economic challenges, such as climate change, that pre-date the pandemic.
Source: International Labor Organization
The report examines the impacts of the COVID-19 crisis on global and regional trends in employment, unemployment, and labor force participation, as well as on job quality, informal employment, and working poverty. It also offers an extensive analysis of trends in temporary employment both before and during the pandemic.
On the basis of the latest economic growth forecasts, the ILO is projecting that total hours worked globally in 2022 will remain almost 2 percent below their pre-pandemic level when adjusted for population growth,
Posted by at 7:18 AM
Labels: Inclusive Growth
Friday, January 21, 2022
On cross-country:
On the US:
On China
On other countries:
On cross-country:
On the US:
Posted by at 5:00 AM
Labels: Global Housing Watch
Thursday, January 20, 2022
The outbreak of the novel Coronavirus, or COVID-19, has exacerbated economic and social inequalities. Several studies have tried to capture the impact of the same using extensive qualitative and quantitative data, spanning diverse categories like economic backgrounds, geographical regions, sex, caste, color, and other such social identities, inter alia.
The NBER paper, Inequality in the Times of a Pandemic (2022), by Stefanie Stantcheva, maps findings “related to inequalities across the income distribution, sectors and regions, gender, and inequalities in education inputs for children from different socioeconomic backgrounds”.
On similar lines but delving deeper on the issue of income inequalities, the paper, Epidemics, pandemics and income inequality (2022) in Health Economics Review attempts to understand how the outbreak of diseases like the Coronavirus, Ebola, Avian flu, etc., have impacted income distributions in the first two decades of the 21st century. The paper develops a model that indicates a positive association between these health crises and income inequality. To empirically test theoretical predictions, it explores the effect on the Gini coefficient of a dummy variable that indicates the occurrence of an epidemic or a pandemic in a country in a given year and the number of deaths per 100,000. To properly address potential endogeneity, the authors implement a Three-Stage-Least Squares technique. The estimation shows that the number of deaths per 100,000 population variable has a statistically significant positive effect on the Gini coefficient, especially when COVID-19 data is included.
The outbreak of the novel Coronavirus, or COVID-19, has exacerbated economic and social inequalities. Several studies have tried to capture the impact of the same using extensive qualitative and quantitative data, spanning diverse categories like economic backgrounds, geographical regions, sex, caste, color, and other such social identities, inter alia.
The NBER paper, Inequality in the Times of a Pandemic (2022), by Stefanie Stantcheva, maps findings “related to inequalities across the income distribution,
Posted by at 8:13 AM
Labels: Inclusive Growth
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