Growth, Inequality and Poverty in Selected Caribbean and Latin American Countries, with Emphasis on Guyana

1998 ◽  
Vol 30 (3) ◽  
pp. 591-617 ◽  
Author(s):  
JOHN GAFAR
Keyword(s):  
Economic Growth ◽  
Human Development ◽  
Latin American ◽  
Human Development Index ◽  
Direct Relationship ◽  
Poverty Line ◽  
Level Of Education ◽  
The Poor ◽  
Per Capita ◽  
Latin American Countries

The statistical evidence surveyed suggests that as an indicator of development the Human Development Index is directly related to the level of per capita income; that inequality is countercyclical; and that economic growth is poverty reducing. In the case of Guyana the data suggest that nearly 43 per cent of the population were below the poverty line (approximately US$1 per day per person); that poverty is predominantly rural; that most of the poor seek employment in agriculture or in the informal (self employed) sector; and that there is a direct relationship between the level of education, health and poverty.

scholarly journals ANALISIS PENGARUH INDEKS PEMBANGUNAN MANUSIA, PDRB PER KAPITA, DAN JUMLAH PENGANGGURAN TERHADAP JUMLAH PENDUDUK MISKIN DI PROVINSI JAMBI

2018 ◽  
Vol 2 (1) ◽  
pp. 165
Author(s):  
Yunie Rahayu
Keyword(s):  
Human Development ◽  
Human Development Index ◽  
Linear Regression Analysis ◽  
Geographic Location ◽  
Least Square ◽  
Gdp Per Capita ◽  
Development Index ◽  
The Poor ◽  
Per Capita ◽  
Poor Population

Poverty is a problem faced by all countries in the world, especially the developing countries, such as Indonesia. Poverty is a complex issue that is affected by a variety of interrelated factors, such as people's income levels, unemployment, health, education, access to goods and services, geographic location, gender, and location the environment. The number of poor population in Central Java is relatively lebihtinggi compared to laindi province of Indonesia, that is occupying ranked second in the number of poor population the largest in Indonesia after East Java. This research aims to analyze how and how much the variable influences the human development index, GDP per capita, and the number of poor population against unemployment in Jambi province in the year 2016. Methods of analysis in this study using multiple linear regression analysis with the method of Ordinary Least Square (OLS) that use data between spaces (cross section) district/town in Jambi province year 2016 with the help of software Eviews 4.1. The results of this research indicate that the variable is the human development index (HDI) a negative and significant effect against the poor population in the province of Jambi, the per capita GDP is negative and significant effect against the number of poor population in The province of Jambi, the unemployment and the number of positive and significant effect against the poor population in the province of Jambi.Keywords: population of the poor, the human development index (HDI), GDP per capita, and the number of Unemployed

scholarly journals ANALISIS FAKTOR YANG MEMPENGARUHI HUMAN DEVELOPMENT INDEX (HDI) PADA 6 DAERAH TERTINGGAL DI PULAU JAWA TAHUN 2010-2016

2017 ◽  
Vol 15 (2) ◽  
pp. 113
Author(s):  
Yunita Firdha Kyswantoro
Keyword(s):  
Economic Growth ◽  
Labor Force ◽  
Human Development ◽  
Human Development Index ◽  
Random Effect ◽  
Random Effect Model ◽  
Poor People ◽  
Development Index ◽  
Per Capita ◽  
Force Variable

Disadvantaged areas are districts whose areas and communities are less developed when compared to other regions on a national scale. Java Island as the contribution of the highest economic growth in Indonesia in fact accounted for 6 of 122 disadvantaged areas in Indonesia, namely Kab. Bondowoso, Kab. Situbondo, Kab. Bangkalan, Kab.Sampang, Kab. Pandeglang, Kab. Lebak. One of the criteria of disadvantaged areas is human resources, this can be measured through HDI (Human Development Index). The number of poor people, labor force and GRDP per capita are some factors that are considered to illustrate the influence of HDI in 6 disadvantaged areas. This research used Random Effect Model (REM) panel data regression in 6 disadvantaged areas in Java Island 2010 - 2016. The result of this research, labor force variable has no significant effect to Human Development Index (HDI). While the number of poor and PDRB perkapita have a significant effect on HDI in 6 disadvantaged areas in Java. It is therefore an effective way to accelerate the growth of economic growth in underdeveloped areas related to HDI through the decline of the number of poor people with the creation of labor-intensive jobs which in turn will increase the per capita GDP. Thus, increasing GRDP per capita will increase Human Development Index (HDI) where HDI is one indicator in economic growth of a region.

scholarly journals Does FDI promote Economic Growth and Development? Evidence from Latin America and Africa

2015 ◽  
Vol 44 (1) ◽  
pp. 34-52
Author(s):  
Mohammed Seid Hussen
Keyword(s):  
Economic Growth ◽  
Human Development ◽  
Latin American ◽  
Positive Impact ◽  
Absorption Capacity ◽  
Transport Infrastructure ◽  
Panel Regression ◽  
Economic Policies ◽  
The Impact ◽  
Latin American Countries

This paper is an attempt to analyse and empirically estimate the impact of FDI on economic growth and human development of Africa and Latin American countries for the period 1985–2011. To this end we develop two equations: growth and human development. Our findings, based on fixed effect panel regression, thus, suggest that FDI does not have a positive impact on economic growth but it has significant positive impact on human development. We conclude that for FDI to be a noteworthy provider to economic growth, it is important to increase absorption capacity by improving the level of democracy, increasing and improving transport infrastructure and following appropriate economic policies. Our results are found to be robust across approach, model specifications and statistical test.

scholarly journals MEMODELKAN KEMISKINAN PENDUDUK PROVINSI BALI DENGAN REGRESI DATA PANEL

2018 ◽  
Vol 7 (3) ◽  
pp. 219
Author(s):  
KADEK BUDINIRMALA ◽  
NI LUH PUTU SUCIPTAWATI ◽  
KETUT JAYANEGARA ◽  
I PUTU EKA NILA KENCANA
Keyword(s):  
Economic Growth ◽  
Human Development ◽  
Human Development Index ◽  
Total Population ◽  
Panel Data Analysis ◽  
Fixed Effect Model ◽  
Poor People ◽  
Development Programs ◽  
Development Index ◽  
The Poor

One indicator of the success of development programs undertaken is the declining percentage of the poor, defined as the ratio of the number of people classified as poor to the total population. For Bali province, despite its economic growth is higher than national rate; 6.03 percent and 6.24 percent compared to 4.88 percent and 5.02 percent in 2015 and 2016, respectively; the poor are still observed in this province by 4.15 percent of its 4.2 million population in September 2016. In order to make development programs in Bali more effective to decrease the number of poor people, significant determinants of poor have to be recognised. The purpose of this work is to model and to determine the significant factor(s) that affect the percentage of poor in Bali province by applying panel data analysis. Percentage of poor for period 2007 to 2015 is positioned as the dependent variable while economic growth, unemployment rate, labor force participation rates, total population, and human development index as the independent ones. We found the best model to describe the causal relationship among variables is fixed effect model and two predictors, the economic growth rate and human development index, were significant in affecting the number of poor in Bali province.

scholarly journals Capital Formation in Machinery in Latin America, 1890-1930

2009 ◽  
Vol 69 (4) ◽  
pp. 928-950 ◽  
Author(s):  
Xavier Tafunell
Keyword(s):  
Economic Growth ◽  
Latin America ◽  
Latin American ◽  
Rapid Growth ◽  
Capital Formation ◽  
Annual Series ◽  
Per Capita ◽  
Latin American Countries

Investment in machinery is a key component in the analysis of long-term economic growth during the spread of industrialization. This article offers consistent annual series on the magnitude of machinery imports per capita into all Latin American countries for the period 1890-1930. Analysis of these series shows that machinery imports diverged across countries from 1890 through 1913. After 1913 a number of the more backward countries experienced rapid growth in machinery imports. These large differences in machinery investment contributed to unequal development across the Latin American countries.

scholarly journals How is the dynamic impact of Undervaluation on Economic Growth in Latin American Countries?: A Panel VAR analysis

2020 ◽  
Author(s):  
CESAR CHAVEZ
Keyword(s):  
Economic Growth ◽  
Exchange Rate ◽  
Real Exchange Rate ◽  
Latin American ◽  
Panel Var ◽  
Causality Test ◽  
Vector Autoregressive ◽  
The Real ◽  
Per Capita ◽  
Latin American Countries

Abstract In this research, I analyze the dynamic effects of undervaluation on the economic growth per captai of Latin American countries with a period 1980-2018. To estimate these effects, I use a Panel Vector Autoregressive (PVAR) whose estimator is System GMM. The undervaluation variable is created from different measures of the real exchange rate and I also use various measures of GDP per capita to calculate economic growth per capita. I include as control variables macroeconomic and human capital variables to control the different channels of spread of undervaluation on economic growth per capita. The results show that there is a positive effect depending on the definition of the real exchange rate used to calculate the undervaluation. In the results I include the Granger causality test, stability test and impulse response graphs in which I project the response of per capita economic growth to an undervaluation shock.

The effects of corruption on growth, human development and natural resources sector: empirical evidence from a Bayesian panel VAR for Latin American and Nordic countries

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Dante A. Urbina ◽  
Gabriel Rodríguez
Keyword(s):  
Economic Growth ◽  
Natural Resources ◽  
Error Correction ◽  
Human Development ◽  
Latin American ◽  
Nordic Countries ◽  
Var Model ◽  
Panel Var ◽  
Content Type ◽  
Latin American Countries

PurposeThe purpose of this paper is to analyze the effects of corruption on economic growth, human development and natural resources in Latin American and Nordic countries.Design/methodology/approachUsing the hierarchical prior of Gelman et al. (2003), a Bayesian panel Vector AutoRegression (VAR) model is estimated. In addition, two alternative approaches are considered, namely, a panel error correction VAR model and an asymmetric panel VAR model.FindingsThe results reveal some relevant contrasts: (1) in Latin America there is support for the sand the wheels hypothesis in Bolivia and Chile, support for the grease the wheels hypothesis in Colombia and no significant impact of corruption on growth in Brazil and Peru, while in Nordic countries the response of growth to shocks in corruption is negative in all cases; (2) corruption negatively affects human development in all countries from both regions; (3) corruption tends to spur natural resources sector in Latin American countries, while it is detrimental for natural resources sector in Nordic countries.Research limitations/implicationsThe panel VAR approach uses recursive scheme identification. The authors have analyzed robustness using alternative ordering of the variables. The authors also have followed two alternatives suggested by the Referee: a panel error correction VAR model and a panel asymmetric VAR model. However, another more sophisticated identification scheme could be used. Also other variables could be introduced in the VAR model.Practical implicationsRegardless of the issue of the “grease” vs the “sand the wheels” debate, corruption should be reduced because it is anyway harmful for human development. The differences in the results for Latin American and Nordic countries show that the effects of corruption have to be assessed considering the different institutional and economic conditions of the countries analyzed.Social implicationsGovernments should seek to reduce corruption because, despite corruption can have mixed effects on economic growth in some contexts, it is anyway harmful for human development. Besides, the finding that in some Latin American countries more activity in the extractive industries is generated by means of corruption confirm the association between corruption and extractivism found by Gudynas (2017) and can explain why there are issues of environmental damage and social conflict linked to natural resources in those countries.Originality/valueThe present study contributes to the literature by presenting evidence on the effects of corruption on growth, human development and natural resources sector in Latin American and Nordic countries. It is the first study on economics of corruption which directly compares Latin American and Nordic countries. This is relevant because there are important differences between both regions since Latin American countries tend to suffer from widespread corruption, while the Nordic ones have a high level of transparency. It is also the first in using a Bayesian panel VAR approach in order to evaluate the effects of corruption.

scholarly journals Analysis of Energy Poverty in 7 Latin American Countries Using Multidimensional Energy Poverty Index

Energies ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1608 ◽  
Author(s):  
Oscar S. Santillán ◽  
Karla G. Cedano ◽  
Manuel Martínez
Keyword(s):  
Human Development ◽  
Latin American ◽  
Human Development Index ◽  
Research Question ◽  
Actual State ◽  
Clear Correlation ◽  
Poverty Index ◽  
Energy Poverty ◽  
The World ◽  
Latin American Countries

Energy poverty is a serious problem affecting many people in the world. To address it and alleviate it, the first action is to identify and measure the intensity of the population living in this condition. This paper seeks to generate information regarding the actual state of energy poverty by answering the research question: is it possible to measure the intensity of energy poverty between different Latin American countries with sufficient and equivalent data? To achieve this, the Multidimensional Energy Poverty Index (MEPI), proposed by Nussbaumer et al., was used. The results present two levels of lack of access to energy services: Energy Poverty (EP) and Extreme Energy Poverty (EEP). The last one, is a concept introduced by the authors to evaluate energy poverty using MEPI. Results of people living on EP (EEP within parentheses) are as follow: Colombia 29% (18%), Dominican Republic 32% (14%), Guatemala 76% (61%), Haiti 98% (91%), Honduras 72% (59%), Mexico 30% (17%) and Peru 65% (42%). A clear correlation between the Human Development Index (HDI) and MEPI is displayed, however some countries have relatively high values for the HDI, but do not perform so well in the MEPI and vice versa. Further investigation is needed.

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