Alessio Moro

BIASED TECHNICAL CHANGE, INTERMEDIATE GOODS, AND TOTAL FACTOR PRODUCTIVITY

Biased technical change can be defined as changes that affect the elasticity of output with respect to inputs. In this paper, I analyze the effect of biased technical change on total factor productivity (TFP). I construct an input-output economy in which firms produce gross output using capital, labor and intermediate goods. In equilibrium, biased technical change appears as an explicit part of TFP in the value added aggregate production function, where the latter is obtained through the aggregation of individual firms optimal decisions. A larger elasticity of gross output with respect to intermediates implies a smaller TFP level. I use the model to quantify the impact of biased technical change for measured TFP growth in Italy. The exercise shows that biased technical change can account for the productivity slowdown observed in Italy from 1994 to 2004.

Money Dynamics with Multiple Banks of Issue: Evidence from Spain 1856-1874

This paper analyzes the Spanish monetary system from 1856, when the Bank of Spain was created, to 1874, when it was awarded the monopoly of emission. This period was characterized by the emergence of an unregulated banking system, with multiple banks of issue entitled to emit bank notes. We focus on two main issues: i) the large fluctuations in the money supply during this period; and ii) the lack of a lender of last resort in the banking panic of 1866. To analyze this, we construct a new dataset on money supply aggregates. The paper also estimates the economic impact of monetary fluctuations with the help of a calibrated new Keynesian model. Our results suggest that money supply shocks had a milder effect on inflation and output than the one predicted by the theory.

Does TFP drive Housing Prices? A Growth Accounting Exercise for Four Countries

Housing prices diverge from construction prices after 1997 in four major countries. Besides, TFP differences between construction and the general economy account for the evolution of construction prices in the U.S. and Germany, but not in the U.K. and Spain.

The role of gender in employment polarization

We document that U.S. employment polarization in the 1980-2008 period is largely generated by women. Female employment shares increase both at the bottom and at the top of the skill distribution, generating the typical U-shape polarization graph, while male employment shares decrease in a more similar fashion along the whole skill distribution. We show that a canonical model of skill-biased technological change augmented with a gender dimension, an endogenous market/home labor choice and a multi-sector environment accounts well for gender and overall employment polarization. The model also accounts for the absence of employment polarization during the 1960- 1980 period and broadly reproduces the different evolution of employment shares across decades during the 1980-2008 period. The faster growth of skill-biased technological change since the 1980s accounts for most of the employment polarization generated by the model.

Development, Growth and Volatility

Does GDP composition affect GDP growth and volatility? Typically, economies at advanced stages of development grow slower, are less volatile and have a larger share of services in GDP with respect to economies at middle stages. I propose a theory of development consistent with these three facts. I show that even when total factor productivity (TFP) growth and volatility are the same in manufacturing and services at the gross output level, the larger intensity of intermediate goods in gross output production in manufacturing implies a larger growth and volatility of TFP at the value added level in manufacturing than in services. As GDP is a weighted average of value added of the sectors in the economy, a larger share of services in the economy implies both a smaller GDP growth and a smaller GDP volatility. Numerical results suggest that along a transition path in which the share of services increases from 0.41 to 0.73, the same gross output TFP process in manufacturing and services implies a per-capita GDP growth and volatility 21% and 18% larger in the first part of the transition with respect to the second. These numbers represent 95% of the difference in per-capita GDP growth and 95% of the difference in per-capita GDP volatility between middle and high income economies during the 1970-2006 period. Also, the model can account for 58% of the per-capita GDP growth and 32% of the per-capita GDP volatility differences measured in the U.S. between the 1950-1978 and 1979-2007 periods.