Essays in Applied Macroeconomics

par Mario Pietrunti

Thèse de doctorat en Sciences économiques

Sous la direction de Patrick Fève.

Soutenue le 29-06-2016

à Toulouse 1 , dans le cadre de Toulouse School of Economics (Toulouse) , en partenariat avec TSE-R (Toulouse) (équipe de recherche) .

  • Résumé

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  • Résumé

    This thesis investigates three different issues in applied macroeconomics. In the first chapter (co-authored with Roberto Pancrazi) we document that long-run expectations of both households and, especially, financial intermediaries about future housing prices had a large impact on households’ home equity extraction during the pre-crisis boom in U.S. housing prices. Using a model of collateralized credit market populated by households and banks we find that: (1) mild variations in long-run forecasts of housing prices result in quantitatively considerable differences in the amount of home equity extracted during the boom; (2) the equilibrium levels of debt and interest rate are particularly sensitive to financial intermediaries’ expectations. In the second chapter (co-authored with Patrick Fève), we investigate the macroeconomic effects of fiscal policy in a setting in which private agents receive noisy signals about future shocks to government expenditures. We show how to empirically identify the relative weight of news and noise shocks to government spending and compute the level of noise for Canada, the UK and the US. Embedding imperfect fiscal policy information in a mediumscale DSGE model, we find that with a persistent change in expected public spending, the existence of noise (as estimated using actual data) implies a sizable difference in fiscal multipliers compared to the perfect fiscal foresight case. The third chapter studies the impact on the real economy of frictions stemming from the financial sector. First a non-linear medium scale DSGE with real and nominal rigidities is solved, where the non-linearity is induced by an occasionally binding constraint on banks’ capital. Then likelihood-free methods are used to estimate the model on Italian data from 1999 to 2014.A key result is that the non-linear the model is able to generate business cycle asymmetries observed in actual data that cannot replicated with linear v models. The model is then used for testing the usefulness of various macroprudential policies, finding that taxing banks’ leverage proves to be rather effective in smoothing the volatility of real variables, although there is no one-size-fits all policy, as each of them has a different impact on various features of the business cycle.

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