The Lack of Convergence of Latin-America Compared with CESEE

Bakker, Bas; Ghazanchyan, Manuk; Ho, Alex; Nanda, Vibha

doi:10.5089/9781513547886.001

Cited by 3 publications

(2 citation statements)

References 31 publications

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“…Labor and total factor productivity growth have lagged other emerging markets and developing economies. This is in part linked to significant structural constraints, including inadequate infrastructure, high levels of informality, low levels of human capital, and weak governance (Bakker et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

The Macroeconomic Effects of Structural Reforms in Latin America and the Caribbean

David

Komatsuzaki²,

Pienknagura³

et al. 2020

IMF Working Papers

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This paper estimates the macroeconomic effects of structural reforms in Latin America and the Caribbean (LAC) using the dataset constructed by Alesina et al. (2020). We find that large changes in the reform index have positive effects on GDP and employment that reach 2 percent after 5 years. Furthermore, reforms boost investment, exports, imports, and reduce export concentration, in addition to favoring tradable sectors. Nonetheless, the results also indicate that the effects of reforms have not been uniform across different segments of the population. These findings bring to the forefront the need to consider accompanying policies to ensure that reforms promote inclusive growth. Moreover, evidence from country case studies using the synthetic control method point to heterogeneous effects of reforms on income per capita.

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Section: Introductionmentioning

confidence: 99%

The Macroeconomic Effects of Structural Reforms in Latin America and the Caribbean

David

Komatsuzaki²,

Pienknagura³

et al. 2020

IMF Working Papers

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“…Bakker et al (2020) emphasizes the roleof himan capital in explaining lack of convergence in Latin America.…”

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confidence: 99%

Will the AI Revolution Cause a Great Divergence?

Alonso¹,

Berg²,

Kothari³

et al. 2020

IMF Working Papers

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This paper considers the implications for developing countries of a new wave of technological change that substitutes pervasively for labor. It makes simple and plausible assumptions: the AI revolution can be modeled as an increase in productivity of a distinct type of capital that substitutes closely with labor; and the only fundamental difference between the advanced and developing country is the level of TFP. This set-up is minimalist, but the resulting conclusions are powerful: improvements in the productivity of “robots” drive divergence, as advanced countries differentially benefit from their initially higher robot intensity, driven by their endogenously higher wages and stock of complementary traditional capital. In addition, capital—if internationally mobile—is pulled “uphill”, resulting in a transitional GDP decline in the developing country. In an extended model where robots substitute only for unskilled labor, the terms of trade, and hence GDP, may decline permanently for the country relatively well-endowed in unskilled labor.

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Effect of Education on the Economic Income of Households in Peru, Application of the Mincer Theory in Times of Pandemic (COVID-19)

et al. 2022

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The objective was to determine the effect of education on the economic income of households in Peru in times of the pandemic (COVID-19), for which a quantitative research approach was applied, of a non-experimental type and of descriptive-correlational design; the econometric model of log-linear type was used, based on the Mincer equation, with the information from the database of the National Household Survey, for the period of 2021. The economic income on average was 275.96 soles, with a standard deviation of 1451.41 soles, with high variability, identifying very precarious economic income ranging from 15.00 to 15,000.00 soles/month per worker; the years of schooling of the worker on average were 12 years, showing the scope of complete secondary training, with a population without years of education, and on the contrary, there are workers with postgraduate education, with the variability of 4 years. Finally, the effect of education measured through years of schooling on economic income is positive, or direct, since education explains 14.34% of economic income; the experience of the worker, gender, area of residence, age and marital status, in the same way, have a positive effect on economic income, strongly highlighting gender and area of residence which explain 19.86% and 30.45% of the economic income in the household in Peru.

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The Lack of Convergence of Latin-America Compared with CESEE

Cited by 3 publications

References 31 publications

The Macroeconomic Effects of Structural Reforms in Latin America and the Caribbean

The Macroeconomic Effects of Structural Reforms in Latin America and the Caribbean

Will the AI Revolution Cause a Great Divergence?

Effect of Education on the Economic Income of Households in Peru, Application of the Mincer Theory in Times of Pandemic (COVID-19)

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