Nonlinear Growth and the Productivity Slowdown

In this paper we study the productivity slowdown taking as a starting point the nonlinear shape of the growth path. We relate the slowdown to the evolution of the world income distribution in the periods before and after the oil shock of 1973 and show that: i) in both periods growth is nonlinear; ii) the productivity slowdown consists in a downward shift of the nonlinear growth path; iii) in both periods we observe a medium-run tendency to polarization, but the long-run distribution features convergence in the first period and polarization in the second. We provide theoretical and empirical arguments suggesting that the interaction between nonlinear growth and international technology spillovers can explain how a temporary shock may have permanent effects on world growth.

Productivity Polarization and Sectoral Dynamics in European Regions

We show that the distribution dynamics of productivity in European regions displays polarization with a nonlinear growth path. We investigate the factors explaining this behavior focusing in particular on sectoral composition. The beta-convergence analysis reveals that initial shares of Manufacturing and Other Market Services have a nonlinear impact on growth, while spatial effects are not statistically significant. By decomposing the dynamics of aggregate productivity in terms of sectoral dynamics, we show that productivity in Manufacturing, Non Market Services, and Other Market Services does not converge, for the complex interaction of technological spillovers and specialization effects

SHOOTING DOWN THE PRICE: EVIDENCE FROM MAFIA HOMICIDES AND HOUSING MARKET VOLATILITY

In this work, we assess the role of a specific type of organized crime in influencing choices on where living within the city territory, and consequently, volatility in house prices. More specifically, we test how organized crime killing may influence house pricing behaviors. Firstly, we show evidences about how organized crime is associated with higher inequality of housing prices for Italian cities in 2011. Then, by collecting and geo referencing data on the city of Naples for the period 2002-2016, we test for the direct influence of homicides on the relevant territory, as on the neighboring districts. Results show a negative and significant impact of killing on the house prices either for sales or for rents and a positive effect in neighboring district, driving increases in within-city inequality

Counterfactual Distribution Dynamics across European Regions

This paper proposes a methodology which combines elements of parametric regression analysis with the nonparametric distribution dynamics approach in order to analyse the role of some variables in the convergence of productivity across European regions over the period 1980-2002. We find that the initial productivity crucially accounts in the convergence process across European regions. Differently, employment growth seems not to play a role, while the Structural and Cohesion Funds seem to play a positive role, even though such effect seems to be very low and statistically significant only at the low bound of the range of initial productivity. The structural change of regional economies plays a positive role, but such effect is statistically significant only for the least productive regions. The output composition of a region in 1980 affects the convergence process of productivity growth in several ways. In particular, the share of non market services on output acts like a source of convergence from 1980 to 2002 but in the long-run it plays a negligible role. Finally, the share of finance acts like a force of divergence across European regions, especially for the least productive regions

On the Determinants of Distribution Dynamics

n this paper we propose a novel approach to identify the impact of growth determinants on the distribution dynamics of productivit y. Our approach integrates counterfactual analysis with the estima tion of stochastic kernels. The counterfactuals are constructed from a semi-parametric growth regression, in which the cross-section heterogeneity in the growth determinants is removed. The methodology also allows us to test for potential distributional effects in the residuals. We illustrate the usefulness of the proposed methodology by an application to a cross-section of countries, which highlights the significant impact on inequality and polarization in the world productivity distribution of growth determinants from an augmented Solow model

World Interest Rates, Inequality and Growth: an Empirical Analysis of the Galor-Zeira Model

Following Galor and Zeira (1993), we study the effect of the world interest rate on inequality and growth for the period 1985-2005, characterized by falling world interest rates and cross-country income polarization. We argue that the two phenomena are related on th e basis of the following findings, which are in accordance with the predictions of the Galor and Zeira model: 1) a reduction of the world inter est rates increases inequality in rich countries and decreases inequ ality in poor countries; 2) inequality has a negative (and significant) eff ect on human capital accumulation in rich countries and a positive (b ut mostly not significant) effect in poor countries; 3) human capital po sitively affects GDP in both group of countries, in particular with a higher marginal effect in poor countries. The overall effect of these facts is polarization in the world income distribution

On the Determinants of Distribution Dynamics

n this paper we propose a novel approach to identify the impact of growth determinants on the distribution dynamics of productivit y. Our approach integrates counterfactual analysis with the estima tion of stochastic kernels. The counterfactuals are constructed from a semi-parametric growth regression, in which the cross-section heterogeneity in the growth determinants is removed. The methodology also allows us to test for potential distributional effects in the residuals. We illustrate the usefulness of the proposed methodology by an application to a cross-section of countries, which highlights the significant impact on inequality and polarization in the world productivity distribution of growth determinants from an augmented Solow model

DEEP AND PROXIMATE DETERMINANTS OF THE WORLD INCOME DISTRIBUTION

This paper studies the deep and proximate determinants of the evolution of the cross‐country distribution of GDP per worker in the period 1960–2008 by a novel method based on an information criterion. We find that countries of our sample follow three distinctive growth regimes identified by two deep determinants, namely life expectancy at birth in 1960 and the share of Catholics in 1965, and that each regime is characterized by non‐linearities. Growth regimes appear to be the main cause of the increased inequality and polarization, while technological catch‐up, proxied by the initial level of GDP per worker, acts in the opposite direction. Finally, human capital marginally reduces polarization, while investment rates and employment growth have no distributional effect

Organized Crime, Corruption and Economic Growth

In this paper we study the relationship between organized crime, corruption and economic growth. To shed light on this nexus, we propose a growth model in which organized crime can embezzle public spending by corrupting and threatening public officers. Then we bring the empirical implications of the model to data from Italian regions, as stylized facts show that less developed regions are characterized by the highest levels of corruption and of presence of criminal organizations of Mafia-type. Our main findings are: i) the per capita GDP dynamics of Italian regions in the period considered is characterized by multiple regimes identified by the initial level of organized crime, a finding consistent with a multiple steady state growth dynamics (e.g. Durlauf and Johnson, 1995); ii) in the regions with the higher levels of organized crime the estimated share of embezzled public expenditure is higher and, moreover, public expenditure has a negative effect on per capita GDP. Differently, in the regions with lower levels of organized crime the estimated share of embezzled public expenditure is lower and the effect of public expenditure on per capita income is positive