A measurement of affluence and poverty interdependence across countries: Evidence from the application of tail copula

This paper examines affluence and poverty interdependence across 185 countries and its evolution over 1969–2014. To estimate affluence and poverty interdependence and derive tail interdependences the tail copulae are applied to multivariate density function. The tail coefficients are estimated in the non-parametric way as in Schmidt and Stadtmüller (2006). The estimates show, that poverty is less interdependent and continue to decrease, while affluence has asymptotically high global dependence, meaning a higher global dependence on and sensitivity to the well-being of the affluent countries. The received results derive the pattern of the extreme interdependence and can help to identify poverty and affluence spill-over across countries and regions and calculate the average sensitivity of a country to these phenomena on the global level and can potentially help in poverty reduction strategies within the Sustainable Development Goal by the United Nations.     

Estimating Lower Tail Dependence Between Pairs of Poverty Dimensions in Europe

This article provides an innovative method for measuring the dependence between pairs of poverty dimensions using a semiparametric copula approach that permits us to account for the importance of extreme low values. The association between pairs of poverty dimensions at the lower tail is easily measured using the parameter estimates of the specified parametric copula, and no further calculations are needed. This approach is used to measure the bivariate lower tail dependence between the dimensions of the AROPE rate in Europe at two time points (2009 and 2018). The findings reveal a statistically significant increase in the lower tail dependence between 2009 and 2018 in several European countries.     

COMPARATIVE WELL-BEING OF CHILDREN AND ELDERLY

This paper compares the economic well-being of children and the elderly to each other in the United States and across six industrialized countries. Using the Luxembourg Income Study database, we find that U.S. children–whose economic status is measured by their family income–are generally worse off than U.S. elderly in terms of both poverty and adjusted mean income. Moreover, U.S. children are worse off in terms of higher poverty rates than are the children in any of the other countries studied. The paper presents a variety of explanations for these differences.     

Youth Poverty,Employment, and Leaving the Parental Home in Europe

This paper studies the nature of youth poverty dynamics in Europe. First, it analyzes to what extent experiencing poverty in a given period is in itself positively related to the probability of living below the poverty line again in the future. That is, we assess the degree of poverty genuine state dependence among young people. Second, we study the interrelationships between poverty, employment, and residential emancipation. The results show that youth poverty genuine state dependence is positive and highly significant, but this scarring effect is short‐lived in Scandinavia compared to Southern or Continental Europe. Moreover, although we find a strong association between poverty and leaving home in Nordic countries, time spent in economic hardship does not last long. On the contrary, in Spain and Italy, young adults tend to leave their parental home much later in order to avoid falling into a poverty state that is more persistent.     

Does urbanization increase pollutant emission and energy intensity? evidence from some Asian developing economies

This paper aims to investigate the effects of urbanization on pollutant emissions and energy intensity in selected Asian developing countries after controlling for the effects of disaggregated (renewable and non-renewable) energy consumption, trade liberalization, and economic growth. We use both linear and nonlinear panel data econometric techniques and employ recently introduced mean group estimation methods, allowing for heterogeneity and cross-sectional dependence. However, to check the robustness of our panel results, we also apply the autoregressive distributed lag (ARDL)-bound testing approach to country-level data. In addition, the relationship between affluence and CO₂ emissions is examined in the context of the Environmental Kuznets Curve (EKC) hypothesis. The estimation results identify the population, affluence, and non-renewable energy consumption as major factors in pollutant emissions in Asian countries. However, the results of the EKC hypothesis show that when countries achieve a certain level of economic growth, their emissions tend to decline. Whereas nonlinear results show that renewable energy, urbanization, and trade liberalization reduce emissions, linear estimations do not confirm these outcomes. Thus, substitution of non-renewable for renewable energy consumption, cautious and planned urbanization programs and more liberal trading regimes may be viable options for sustainable growth of these developing Asian economies.     

The dependence structure between the Canadian stock market and the USD/CAD exchange rate: a copula approach

Abstract This paper investigates the dependence structure between the real Canadian stock returns and the real USD/CAD exchange rate returns, using the Symmetrized Joe‐Clayton (SJC) copula function. We estimate the SJC copula with monthly data over the period 1995:1 to 2006:12. Our results show significant asymmetric static and dynamic tail dependence between the real stock returns and the real exchange rate returns, such that the two returns are more dependent in the left than in the right tail of their joint distribution. We explain this asymmetric dependence in terms of an asymmetric interest rate policy by Canadian monetary authorities in response to changes in the real exchange rate during sub‐periods of falling and rising commodity prices.     

LATIN AMERICAN EXCHANGE RATE DEPENDENCIES: A REGULAR VINE COPULA APPROACH

This study implements a regular vine copula methodology to evaluate the level of contagion among the exchange rates of six Latin American countries (Argentina, Brazil, Chile, Colombia, Mexico, and Peru) from June 2005 to April 2012. We measure contagion in terms of tail dependence coefficients, following Fratzscher's (1999) definition of contagion as interdependence. Our results indicate that these countries are divided into two blocks. The first block consists of Brazil, Colombia, Chile, and Mexico, whose exchange rates exhibit the largest dependence coefficients, and the second block consists of Argentina and Peru, whose exchange rate dependence coefficients with other Latin American countries are low. We also found that most of the Latin American exchange rate pairs exhibit asymmetric behaviors characterized by nonsignificant upper tail dependence and significant lower tail dependence. These results imply that there exists contagion in Latin American exchange rates in periods of large appreciations, whereas there is no evidence of contagion during periods of currency depreciation. This empirical regularity may reflect the “fear of appreciation” in emerging economies identified by Levy‐Yeyati, Sturzenegger, and Gluzmann (2013). (JEL C32, C51, E42)     

Poverty Reduction through Growth and Redistribution Policies—a Panel Analysis for 59 Developing Countries

In this paper, we empirically test the determinants of growth, as derived from a semi‐endogenous growth model, in terms of its poverty‐reducing effects. We base our empirical analysis of the growth and distribution effect of economic policies on a panel data set of 59 developing countries, divided into two subgroups, and a sample period ranging from 1960 to 2004. For purposes of estimation we make use of the generalized methods of moments (GMM) system estimator. The estimations reveal a poverty‐reducing effect of investment. In contrast population growth induces higher poverty. The import of knowledge is growth enhancing only for countries at a higher stage of development—meanwhile the positive growth effect of an increasing democratization is limited to the poor developing countries.     

Portfolio Diversification Strategy Via Tail‐Dependence Clustering and ARMA‐GARCH Vine Copula Approach

This study proposes a diversified portfolio construction method based on the tail dependence between the financial assets and adopting both market prior information and the exports’ subject views. In this paper, tail‐dependence clustering was applied to divide candidate assets into different groups according to their tail dependence during the crisis period and the ARMA‐GARCH vine copula‐opinion pooling approach was applied to select the minimum Conditional Value‐at‐Risk portfolio according to the clustering results. The daily closed prices of the components of DAX 20 from 3 January 2006 to 20 December 2014 were studied to illustrate the methodology. The results reveal that more than 90% of 450 possible portfolios are modelled by D‐vine structure and Student's t‐copula dominates almost all the cases for pair copula selection. As Student's t‐copula captures the symmetric tail dependence, the 450 possible portfolios do not show stronger lower tail dependence than upper tail dependence. This study contributes by combining cluster analysis with portfolios selection. It uses vine copula to capture the dependence structure among assets. Finally, it offers a flexible method to describe market and offers a strategy to construct diversified portfolios by adding the investors’ information into portfolio selection procedure at the 1‐day forecast horizon.     

Equal opportunity and poverty reduction: How should aid be allocated?

This paper analyzes a model of aid allocation equalizing the opportunity between recipient countries to reach a common poverty reduction goal. We propose a fair and efficient aid allocation based on a multicriteria principle. The model considers structural handicaps in recipient countries in terms of lack of human capital and economic vulnerability, their initial poverty, and the natural gap between the growth rate required to reach a development goal and the observed one. We show that our proposed aid allocation favors poor and vulnerable countries with our multicriteria principle. It substantially differs from the observed allocation. Analyses also shed light on the impact of the donors' aversion to the low natural growth gap in recipient countries on the optimal aid allocation and the marginal efficiency of aid.     

Modelling the dependence between the times to international adoption of two related technologies

The structure of the dependence between the times to adoption by a country of two related innovations, the fax and the cellular telephone, is modelled in two stages. The first stage is the choice of density function for the time to adoption. The second stage is describing the dependence relation. For the first stage, a Weibull density function is used with its scale factor adapted to account for the economic and technological environments in different countries. Environmental data are collected from several sources. Copulas are used to model the dependence relation, three single parameter copulas are considered, those due to Farlie-Gumbel-Morgenstern (FGM), Frank and Plackett. Their properties are described and a combined estimation of the copula and density function parameters carried out. The limitations of the FGM copula rule it out from further consideration. The other copulas coupled with the Weibull, using eight environmental variables, are shown to provide valuable insights into the effects of environmental variables on adoption times. Given that a country has adopted one technology, the model of the dependence relation is used to provide the conditional density of the time to adoption of the other technology.     

What are the Policy Lessons from Sweden? On the Rise,Fall and Revival of a Capitalist Welfare State

This paper discusses a number of questions with regard to Sweden's economic and political development:

? How did Sweden become rich?

? What explains Sweden's high level of income equality?

? What were the causes of Sweden's problems from 1970 to 1995?

? How is it possible that Sweden, since the crisis of the early 1990s, is growing faster than most EU countries despite its high taxes and generous welfare state?

These questions are analysed using recent insights from institutional economics, as well as studies of inequality and economic growth. The main conclusion is that there is little, if any, Swedish exceptionalism: Sweden became rich because of well-functioning capitalist institutions, and inequality was low before the expansion of the welfare state. The recent favourable growth record of Sweden, including the period of financial stress (2008–10), is a likely outcome of a number of far-reaching structural reforms implemented in the 1980s and 1990s.     

Regional and copula estimation effects on EU and US energy equity portfolios

ABSTRACT

The aim of this paper is to investigate the regional interdependence structure of energy equities in the US and in the EU. Based on weekly stock prices of 28 big energy firms in the two regions from 2008 to 2019, we compare the efficiency of using bivariate or multivariate copulas to describe the dependence structure of energy equities. Furthermore, we investigate the impact of the choice between these two methods on the performance of energy equity portfolios. Our empirical results show that multivariate copulas, such as C-Vine, allow to better describe the dependence structure of energy equities. We also find that there is a stronger and more complex dependence structure among EU energy equities than among US energy equities. Our scenario analysis also shows that the dependence structure is stronger during the GFC while being weaker during the ESDC. More importantly, the correlation matrix obtained from the multivariate copula method allows to obtain optimal mean-CVaR portfolios with a higher performance than that from the bivariate copula method. More importantly, optimal portfolios constituted with multivariate copulas allow to reduce the portfolio’s sensitivity to oil prices.     

Diamonds and precious metals for reduction of portfolio tail risk

ABSTRACT

We study the performance of diamonds compared to gold and other precious metals in mitigating the tail risk of a diversified equity market portfolio over the period June 2007 to October 2018. Our results display a diversification benefit of some diamond indices, which also improve the portfolio reward-to-risk ratio. To corroborate this evidence, we study the dependence structure and tail dependence of diamonds and a broad equity market portfolio and compare it to the dependence obtained with gold and other precious metals. Results from fitting a bivariate copula show that the average left tail dependence reaches its minimum when diamonds are used. We also show that using shares of diamond-mining companies does not provide the same benefits.     

Financial inclusion and poverty: a tale of forty-five thousand households

ABSTRACT

Using a new nationally representative survey data covering approximately 45,000 Indian households, we examine the effects of financial inclusion on poverty. We construct a multidimensional indicator of financial inclusion and examine the effects of financial inclusion on multiple measures of poverty including the household Poverty Probability Index (PPI), household deprivation scores, and poverty line. We find that financial inclusion has a strong poverty-reducing effect. This finding is consistent across the different measures of poverty used, and alternative ways of measures financial inclusion. These results underpin the importance of financial inclusion and the need for its promotion across countries.     

Measurement of Changes in Economic Welfare in India: 1970–2001

This paper provides time series estimates of measures of economic welfare, inequality, decile class specific true cost of living index and poverty measures based on 20 rounds of National Sample Survey data for the period 1970–2001. It has estimated piece-wise Linear Expenditure System (LES) for very poor, moderately poor, non-poor low and non-poor high expenditure groups for rural as well as urban areas. Money metric utility for deciles are derived from the money metric utility function and social welfare index is constructed by aggregating metric utility of the deciles. Using social welfare index as well as real per capita consumption, the paper analyses the changes in economic welfare over the three decades. Using conventional measures, the paper analyses the changes in poverty and inequality during 1970–2001. The paper also provides estimates of the welfare effects of commodity prices.

     

Directional time-varying partial correlation with the Gaussian copula–DCC–GARCH model

This article suggests a directional time-varying partial correlation based on the dynamic conditional correlation (DCC) method. A recent study proposed the copula DCC based on the vine structure. Due to the arbitrary variable selection, their method can produce unnecessary dependence in the multivariate structure, with extra economic and computational burdens. To overcome this limitation, we incorporate directional dependence by copula to track the causal relationship among multiple variables and then extend the copula bivariate DCC method to a directional time varying partial correlation in the multivariate structure. Our proposed method provides a reasonable and efficient conditional dependence structure, without the trial and error process. We offer an application of our method to the U.S. stock market as an illustrated example.     

Measuring and Optimizing Portfolio Credit Risk: A Copula‐based Approach*

In this work, we present a methodology for measuring and optimizing the credit risk of a loan portfolio taking into account the non‐normality of the credit loss distribution. In particular, we aim at modelling accurately joint default events for credit assets. In order to achieve this goal, we build the loss distribution of the loan portfolio by Monte Carlo simulation. The times until default of each obligor in portfolio are simulated following a copula‐based approach. In particular, we study four different types of dependence structure for the credit assets in portfolio: the Gaussian copula, the Student's t‐copula, the grouped t‐copula and the Clayton n‐copula (or Cook–Johnson copula). Our aim is to assess the impact of each type of copula on the value of different portfolio risk measures, such as expected loss, maximum loss, credit value at risk and expected shortfall. In addition, we want to verify whether and how the optimal portfolio composition may change utilizing various types of copula for describing the default dependence structure. In order to optimize portfolio credit risk, we minimize the conditional value at risk, a risk measure both relevant and tractable, by solving a simple linear programming problem subject to the traditional constraints of balance, portfolio expected return and trading. The outcomes, in terms of optimal portfolio compositions, obtained assuming different default dependence structures are compared with each other. The solution of the risk minimization problem may suggest us how to restructure the inefficient loan portfolios in order to obtain their best risk/return profile. In the absence of a developed secondary market for loans, we may follow the investment strategies indicated by the solution vector by utilizing credit default swaps.     

The feminization of poverty: the demographic factor and the composition of economic growth

The concept of the feminization of poverty in the United States is examined from a demographic perspective, in particular by a comparative analysis of poverty among female-headed and other-headed households. The author concludes that the growth of female-headed households has been an important factor in the feminization of poverty and that the gap in relative affluence between female-headed and other households is increasing. She also notes that female-headed households suffer most from economic downturns because of sex segregation in the work force.     

The rich, the poor, and the middle class: Thresholds and intensity indices

This paper contributes to the literature on the measurement of social classes by providing a wealth threshold for distinguishing the rich from the middle class and an intensity index for measuring the extent of affluence within a country. The empirical applicability of this approach is then illustrated with household-level survey data from the Bank of Italy; the results show an unambiguous decline in poverty and an increase in affluence in Italy between 2002 and 2004. Moreover, the findings indicate that social class is statistically linked to age, gender, marital status, household size, education, employment, and geography.