The relationship between inequality and GDP growth: An empirical approach

The aim of this work is to analyze the relationship between inequality and economic growth. The results obtained by previous empirical papers were mixed. Authors such as Persson and Tabellini (1991) or Alesina and Rodrik (1994), in fact, find evidence of a negative relationship between the two variables of interest; on the contrary, Li and Zou (1998) and Forbes (2000) find that greater inequality is associated with faster economic growth. Barro (2000 and 2008) claims that inequality has a positive effect on GDP growth in advanced economies, but has a negative impact in developing ones. The present work considers two samples of OCSE countries; in the full sample 33 countries are analyzed for the 1971-2010 period and inequality data are taken from the UNU-WIDER dataset. In the restricted sample 27 countries are considered for the 1981-2010 period and inequality data from the Luxembourg Income Study are used. The estimation technique employed are fixed effects, random effects and GMM Arellano-Bond. The Gini coefficient has been used as inequality measure and ten-years averages of the data have been computed in order to reduce the problem linked to the limited variability of the Gini coefficient across time. In the case of the fixed effects and the GMM estimates on the full sample, positive and statistically significant estimated coefficients for the inequality measure are obtained. The value ranges from 1.2 to 1.5; this means that a 1% increase in inequality within a country would be followed by a more than proportional increase in the rate of economic growth in the following ten years. All the other estimated coefficients, when statistically significant, take the expected sign and the Sargan test confirms that the over-identifying restriction used for the GMM estimation are valid. However, there is room for further research, in particular by considering that: the relationship between the two variables of interest may be quadratic and not linear, the time horizon considered may significatively influence the estimation results and finally it would be necessary to extend the sample by also including developing countries (non-OCSE members)

Did earnings mobility change after minimum wage introduction? Evidence from parametric and semi‐nonparametric methods in Germany

We analyze the evolution of earnings mobility in Germany between 2011 and 2018. We use transition matrices and parametric and semi-nonparametric copula models to assess the impact of the introduction of the national minimum wage on January 1, 2015, on individual positional persistence in the wage distribution. We find a drop in mobility at the bottom of the distribution. This is confirmed both by the parametric and the semi-nonparametric methods used. Prediction accuracy of the semi-nonparametric model is higher than that of the fully parametric model

Consumption dynamics of Latinos and Asians in the US

We document differences in the degree of partial insurance of consumption vs permanent income shocks between Caucasians, Latinos and Asians in the US. Caucasian and Asian individuals share a rather high degree of partial insurance, Asians being slightly more insured than the Caucasians. On the other hand, Latinos are the less insured group, with around 80% of a permanent income shock reverberating into their consumption

Analytical bias correction for two-step fixed effects models with copula-distributed errors

We derive an analytical bias correction for two-step fixed effects models with copula-distributed errors. We work out the approximate bias correction for the Gaussian copula and present a numerical computation exercise for three other copula families. The results are derived for both n and T large

Life after (Soft) Default

We analyze the impact of soft credit default (i.e. a delinquency of 90+ days) on individual trajectories. Using a proprietary dataset on about 2 million individuals for the years 2004 to 2020, we find that a soft default has substantial and long-lasting (i.e. up to ten years after the event) negative effects on credit score, total credit limit, home-ownership status, and income

Relative wage mobility: A new semi-nonparametric estimation method

The study of wage dynamics over time is more insightful than the analysis of point-in- time inequality measures. In policy-making, indeed, low wage careers instead of low- wage jobs should be at the center of the debate on long-term wage inequality. Many previous studies tried to estimate the degree of wage mobility within an economy; however, they rely on some quite restrictive assumptions. The aim of this thesis is to develop new copula model in order to describe more accurately the wage dynamics and its dependence on the initial position in the distribution and on some individual characteristics. We apply this functional copula model to US data. We find no sound empirical evidence of the existence of a “low-wage trap”. We then apply this model to British and German data, in order to verify whether the institutional setting has a relevant influence on wage mobility. We run separate estimates for the periods before and after the financial crisis that started in 2007, in order to assess whether the main drivers of relative wage mobility changed after the financial turmoil. We find that we mobility patterns significantly changed in Germany, but not in the UK, after the financial crisis, especially for young workers. In the third and last chapter of the thesis, we provide further empirical evidence on the importance of relative wage mobility as a driver of individual job satisfaction

The impact of cyclones on local economic growth: Evidence from local projections

We shed new light on the short-term dynamic effects of cyclones on local economic growth in India. We proxy local GDP growth with night-time light intensity data and construct a cyclone index that varies across months and districts depending on wind speed exposures. Using local projections on highly granular data for the period 1993M1-2011M12, we find that yearly estimations hide large short-term differential impacts and that the negative impact of cyclones is the largest between 4 and 8 months after the event

Productivity and Keynes’s 15-Hour Work Week Prediction for 2030: An Alternative, Macroeconomic Analysis for the United States

This paper analyses Keynes’s 1930 prediction that technical advances would cut people’s working week to 15 h by 2030 and investigates why actual working hours are significantly higher in the United States. Elaborating on Keynes’s forecast to provide a general productivity formula while keeping its simplicity, we ran tests on macro-data from 1929 to 2019 and on estimates for 2030, demonstrating that productivity is surprisingly still insufficient to allow for a reduction in working hours across the US economy. This finding represents a substantial contribution to the literature, which has mostly explained long working hours by means of new consumer needs. Even by using microdata, we show that consumption does not explain the stickiness of working hours to the bottom. Hence, this paper combines a macroeconomic, logical-analytical approach based on historical time series with rigorously constructed time series at the microeconomic level. Finally, we also provide policies to narrow the productivity differential to Keynes’s prediction for 2030 while fostering work-life balance and sustainable growth. To understand long working hours in the US despite technical advances—this being one of our main findings—productivity remains crucial

Priorities for Mediterranean marine turtle conservation and management in the face of climate change

As climate-related impacts threaten marine biodiversity globally, it is important to adjust conservation efforts to mitigate the effects of climate change. Translating scientific knowledge into practical management, however, is often complicated due to resource, economic and policy constraints, generating a knowledge-action gap. To develop potential solutions for marine turtle conservation, we explored the perceptions of key actors across 18 countries in the Mediterranean. These actors evaluated their perceived relative importance of 19 adaptation and mitigation measures that could safeguard marine turtles from climate change. Of importance, despite differences in expertise, experience and focal country, the perceptions of researchers and management practitioners largely converged with respect to prioritizing adaptation and mitigation measures. Climate change was considered to have the greatest impacts on offspring sex ratios and suitable nesting sites. The most viable adaptation/mitigation measures were considered to be reducing other pressures that act in parallel to climate change. Ecological effectiveness represented a key determinant for implementing proposed measures, followed by practical applicability, financial cost, and societal cost. This convergence in opinions across actors likely reflects long-standing initiatives in the Mediterranean region towards supporting knowledge exchange in marine turtle conservation. Our results provide important guidance on how to prioritize measures that incorporate climate change in decision-making processes related to the current and future management and protection of marine turtles at the ocean-basin scale, and could be used to guide decisions in other regions globally. Importantly, this study demonstrates a successful example of how interactive processes can be used to fill the knowledge-action gap between research and management.This work was conducted under FutureMares EU project that received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 869300. The Mediterranean Marine Turtle Working Group was established in 2017 and is continuously supported by MedPAN and the National Marine Park of Zakynthos. The work of AC was supported by the Hellenic Foundation for Research and Innovation (H.F.R.I.) under the “First Call for H.F.R.I. Research Projects to support Faculty members and Researchers and the procurement of high-cost research equipment grant” (Project Number: 2340).Peer reviewe

Financial turmoil and earnings mobility

We analyze how earnings dynamics changed in the US after the financial crisis of 2007- 2009. Differently from most models for earnings mobility, we allow persistence patters to depend semi-nonparametrically on both the past individual position in the distribution and on a set of individual-level covariates. Allowing for more flexibility in the model yields a better fit to the data and permits us to uncover changes in earnings mobility patterns that would otherwise remain hidden. Indeed, at the aggregate level, we find no evidence of changes in individual positional persistence in any part of the earnings distribution after the crisis, both with the parametric and with the semi-nonparametric model. However, the semi-nonparametric copula allows us to uncover an increase in earnings mobility for 45-year-old workers with college degree after the crisis