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CEIS: CENTRE FOR ECONOMIC & INTERNATIONAL STUDIES
Furio Camillo Rosati - Director "Distance Work and Life Satisfaction after the COVID-19 Pandemics" 
CEIS Working Paper No. 566 LEONARDO BECCHETTI, University of Rome Tor Vergata - Faculty of Economics
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GIANLUIGI CONZO, University of Rome Tor Vergata - Department of Economics and Finance
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FABIO PISANI, University of Rome Tor Vergata
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We use data of the 10th European Social Survey containing information on COVID-19 and work at distance. We find that working with employers that accept working from home or place of choice less than before the COVID-19 period impacts negatively and significantly on respondents’ wellbeing. We calculate that the reduction of this opportunity produces a fall of 5.6 percent in the probability of declaring high life satisfaction, the effect being concentrated in the subsample of respondents with work-life balance problems where the magnitude of the impact goes up to a maximum of 11 percent.
Our findings contribute to explain the COVID-19 Easterlin paradox (contemporary occurrence of a sharp fall in GDP and non decrease/increase, in life satisfaction in the first 2020 COVID-19 year in many countries) and the great resignation - the rise of quit rates after COVID-19, partly motivated by absence of offers of hybrid contracts allowing a mix of work in presence and work at distance. "On The Nonlinearity of the Finance and Growth Relation: the Role of Human Capital"
CEIS Working Paper No. 567 ALBERTO BUCCI, University of Milan - Department of Business Policy and Economics
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BOUBACAR DIALLO, Qatar University - College of Business and Economics
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SIMONE MARSIGLIO, University of Pisa
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We analyze the role that human capital plays in driving the non-monotonic relation between economic growth and financial development. At this aim we build a theoretical model of endogenous growth in which the nature of the growth and finance nexus is nonlinear and actually depends on the educational level, which ultimately determines the way through which financial development affects both the productivity and the depreciation of human capital. The dependence of the non-monotonic (i.e., bell-shaped) growth and finance nexus on human capital suggests that there may exist a threshold education level beyond which the sign of the relation changes. We econometrically test such a theoretical prediction in a rich and large data set comprising a cross-section of 133 countries over the period 1970-2011. We rely on the GMM instrumental variable approach to address endogeneity issues, and we consider a large number of control variables. After performing a number of robustness checks, all our results are consistent with the view that human capital helps to explain the nonlinear relationship between finance and growth. In particular, we find support for our theoretical model’s conclusion that financial development may be harmful to economic growth in countries that already have high levels of education, while it may be beneficial in those countries in which human capital is less abundant. "Funding Liquidity and Stocks’ Market Liquidity: Structural Estimation From High-Frequency Data"
CEIS Working Paper No. 568 GIAN PIERO AIELLI, Independent
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DAVIDE PIRINO, Department of Economics and Finance, University of Rome "Tor Vergata"
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In accordance with trade signals that operate in the market, we design a microfounded structural model of price formation that features partially informed and noise traders. The former only have information on whether a trend in the latent price dynamic is underway. Without any trend, the partially informed agents do not trade, and prices do not update unless a noise agent activates. Assuming market efficiency, we impose zero expected net profit per trade. With dedicated parametric assumptions, we analytically derive the model’s likelihood, which allows reliable daily estimates (exclusively based on intra-day transaction prices) of the stocks’ market liquidities and funding liquidity (and their estimation errors). Theory predicates that stocks’ volatilities, stocks’ market liquidities, and funding liquiditymay interact in a non-trivial fashion. To shed light on their nature and mutual influence, we model their dynamics through an MGARCH-VAR process. The model is flexible enough to capture some of the well-known empirical features of financial data, such as fat-tailed distributions and conditional heteroskedasticity. Following an econometric methodology of standard practice in the realized volatility literature, the model is fitted on estimates (obtained fromintra-day data through the structural model estimation) of the daily proxies for stocks’ volatilities, stocks’ market liquidities, and funding liquidity. On a dataset of NYSE stocks, we find significant evidence in favor of four stylized facts: (i) stocks’ volatilities, stocks’ market liquidities, and funding liquidity co-move; (ii) co-movements are stronger when funding liquidity dries up; (iii) stocks with lower volatility are characterized by higher market liquidity, and (iv) funding liquidity restrictions have a stronger impact on stocks’ market illiquidities of high-volatility stocks. | | ^top
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Distributed by Economics Research Network (ERN), a division of Social Science Electronic Publishing (SSEP) and Social Science Research Network (SSRN) Directors ECONOMICS RESEARCH CENTERS PAPERS MICHAEL C. JENSEN
Harvard Business School, SSRN, National Bureau of Economic Research (NBER), European Corporate Governance Institute (ECGI), Harvard University - Accounting & Control Unit
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