UC Irvine

Chapter 1 studies the effects of cyclical changes in U.S. income and wealth inequality on macroeconomic gyrations, shifts in aggregate demand, debt swings, and on the effectiveness of monetary policy. It does so though the lens of a structural model with heterogeneous agents that is brought to the data to jointly explain a set of macroeconomic series and a time-varying dimension of inequality, namely the evolution of the U.S. income and wealth inequality since the 1950s to 2009. The paper shows that changes in income and wealth inequality explain a small fraction of output cycles, operate through persistent changes in Aggregate Demand, and cause large swings in household indebtedness. Despite that influence, changes in income and wealth inequality since the mid-80s to 2009 cannot explain the cyclical debt pileup of that period which is accounted for by credit relaxation. Despite the imbalances of the model in terms of the time-varying and unequal distribution of income and wealth, monetary policy has a small effect on income and wealth inequality, and effectively stabilizes the economy by responding aggressively to inflation even if the observed economy wide fluctuations emanate from changes in income and wealth inequality.

Although the recent dramatic decline of the labor share has attracted a lot of attention, the origins and implications of the historical swings of that share during 1964–2016 still remain unexplored. Chapter 2 fills that void. More specifically, Chapter 2 investigates the driving forces and the implications of the fluctuations in the U.S. labor share. To that end, it considers a structural model featuring various potential drivers of the labor share, such as the relative price of investment, labor unionization, measurement errors etc. To that set of potential drivers, the present work adds production automation aiming to encapsulate routine-biased technological shifts, and shows how to bring the model to the data in order to explain the labor share – something that is not straightforward. The analysis shows that changes in production automation explain about 10% of output fluctuations, a third of the labor share across time, about the entire decline in the labor share since the 1990s, and trigger a countercyclical response in labor hours that cannot be matched by any other conventional aggregate shock in a structural framework.

Chapter 3 sheds lights on the unexplored determinants of the notoriously persistent Euro- Area unemployment from a macroeconomic perspective. More precisely, it quantifies the relative importance of a plethora of drivers of unemployment swings by jointly examining unemployment and wage fluctuations through the lens of a structural model estimated on several wage series to strengthen the identification of shifts in labor market competitiveness. I find that these shifts determine long-run unemployment cycles, but their short-run effect depends on the unemployment–wage co-movement: the stronger the co-movement – as it is in Portugal and Spain compared to Greece and Italy – the lower their effect. Furthermore, the low degree of labor market competitiveness is catalytic for the unemployment spike of the Great Recession. Nevertheless, reforms boosting competition during the recovery period generate subdued wage growth. It is worth mentioning that this paper contributes in the Bayesian estimation of DSGE models as well by applying an ecient treatment of the state space dimensionality. In particular, it borrows an approach from the econometrics literature considering reduced-form models, and operationalizes it within the context of a DSGE model.

Finally, Chapter 4 tackles two unresolved issues in the literature on subdued wage growth. First, not all contributions use the same wage measure, sample period, or economies. Second, all contributions employ reduced-form models impeding a general equilibrium approach that would quantify the relative importance of various driving factors of wage growth. I address those issues by studying the big four Euro-Area economies in a structural framework involving a plethora of disturbances extracted from the data through Bayesian estimation on five wage indicators since the 1990s. More importantly, I pin down the influence of those factors during a particular period of time, namely during output recoveries from troughs. I find a cyclical real wage recovery in Germany after the sovereign debt crisis that is statisti- cally di↵erent from the past and is driven by a weakening in firms’ pricing power despite a productivity slowdown. In contrast, a cyclical (real) wage-less output recovery is observed in France and Italy. In France, the productivity slowdown dominates the weakening in firms’ market power. In Italy, the latter effect along with a demand pick up boosting wages do not suffice to exceed the weakening in workers’ market power. In Spain, cyclical wage growth is positive – the sizable weakening in firms’ pricing power and rising demand exceed the weakening in workers’ market power – only in real terms and not in nominal terms, highlighting the importance of jointly examining price and wage inflation.