Essays on applied macroeconomics

A key policy response after the Global Financial Crisis 2007-09 was to explore information gaps revealed by the crisis and provide appropriate proposals for strengthening data collection so that increasingly demanding decisions could be data-driven. Policymakers often seek answers that are not easily observable. Over the last few years, there has been a significant increase in the use of microdata to address macroeconomic questions such as studying the effect of the unconventional monetary policy adopted by the European Central Bank (ECB) in response to the deflationary consequences of the crisis or the impact of renewed fiscal rules aiming at stimulate growth and debt sustainability in the Euro area. More specifically, understanding how shocks or policy changes on the macro level affect household income, agents’ expectations and economic activity by analyzing the distributional impact of monetary policy on inequality and the effect of fiscal policy news on consumption and investments required the use of microeconomic data in the form of state level data or high-frequency data. An important advantage of this approach for investigating income inequality or the effect of policy news is the ability to control for other contemporary macro shocks and to isolate channels much more effectively than traditional aggregate datasets, and hence more easily test alternative explanations of the same phenomenon. The difficulty of the approach generally lies in the manipulation and translation of large datasets into estimates for the aggregate economy. It is clear that this poses a formidable task, which of course raises the issue of the appropriate source of data and methodology to address such macroeconomic questions. This thesis shows that the benefits of using granular data coming from households surveys and from media coverage can be substantial in assessing the response of macro variables. Overall, the contribution of this work is for the development of a more integrated approach in which both micro and macro dimensions complement each other. In this regard, the thesis comprises two chapters that embodied two different projects. Both studies are based on the use of micro data for macroeconomic analysis. The first chapter investigates the effect of standard and non-standard monetary policy implemented by the ECB on income inequality in Italy focusing mainly on the income composition channel and financial channel. The main contribution consists of using the survey micro level data on Income and Living Conditions (EU-SILC, Istat) for the first time in a repeated cross-section experiment to build measures of inequality and the distribution over time for different incomes and subgroups of individuals (savers vs. borrowers). To cover the entire period of ECB communications, that is starting from 1999, we need a longer time span of the series because the survey, alone, covers from 2003 onward. Specifically, we extended the series backwards till 1999, by exploiting the micro data from the Historical Archive of the Bank of Italy’s Survey of Household Income and Wealth (SHIW). To isolate as much as possible the monetary policy surprises, the identification strategy for the monetary innovations is based on intraday interest rates changes around ECB policy announcements available from 1999 onward in the The Euro area Monetary Policy Event-Study Database (EA-MPD), recently published by Altavilla et al. (2019). Finally, we combine micro level data with macro model estimating the monetary policy effects directly on ad hoc inequality indices computed at the individual household level. Dealing with individual households information aggregated at annual level, the local projections is the more suitable econometric technique to evaluate the impact of monetary policy over a short time span by comparing the performance of the impulse response functions of inequality measures in different policy scenarios: 1999-2012 (pre-QE) and 1999-2017 (including the QE period). Overall, evidence suggests that QE is associated with a decrease in Italian household inequality. The second chapter evaluates the effect of a news-based policy shock on consumption and investments in Italy supporting the hypothesis that fiscal policy is largely anticipated and its effects depend on expectations on future policy action. Indeed, fiscal measures in Italy are the result of a complex decision process, entailing long lags between the moment when the decision is taken and when it effectively materializes. Agents modify their actions when they receive signals about changes in exogenous fundamentals, before the time when they are actually implemented. Fiscal anticipation entails difficulties for VAR analysis and it might give rise to a problem of non-fundamentalness due to the potential misalignment between the agents’ and the econometrician’s information set. It means that an informational deficiency problem makes structural inference problematic. To this aim, the contribution to the recent strand of literature on fiscal foresight was to construct a new measure of policy announcements, the Policy News Index (PNI), analyzing textual data from the most important Italian business newspaper (IlSole24Ore) over the period 1997-2019. To disentangle news and noise from fiscal policy communication, the work provides measures of newspaper coverage of policy announcements purged from uncertainty. In this regard, how closely media coverage of fiscal policy impacts real changes on expectations and in macroeconomic conditions is still scarcely debated. Using a Bayesian VAR, analysis investigates whether fiscal news topics are good predictors of fiscal policy actions and to what extent fiscal news coverage exhibits a causality link with consumers’ expectations, consumption and other macro variables. To this purpose, we evaluate the response of households and firms to a news shock on government spending. The innovative feature of this contribution is to use our "news" index alongside other forward-looking variables, i.e. consumer confidence and business climate, as proxy variables of anticipation on economic conditions and business cycle. Furthermore, we apply an identification strategy which differentiates an unanticipated or surprise shock from a foresight or news shock. Differences in the responses to surprise and foresight shocks reflect the role of expectations. Unlike the previous literature on fiscal foresight, results indicate that the "news" or foresight shock has delayed effects on government spending, as well as on consumption and investments. Nevertheless, the "confidence channel" plays a crucial role in anticipating the effect of news on future changes in fiscal policy action.