February 24, 2020
By Christopher Adam and Edward Buffie
We show that a dynamic general equilibrium model with efficiency wages and endogenous capital accumulation in both the formal and (non-agricultural) informal sectors can explain the full range of confounding stylized facts associated with minimum wage laws in less developed countries.
I am actually surprised that minimum wage laws have any bite in countries where the informal sector is substantial and easy to access.
February 18, 2020
By Nicolas Caramp and Dejanir Silva
This paper studies the role of wealth effects in the monetary transmission mechanism in New Keynesian models. We propose a decomposition of consumption that extends the Slutsky equation to a general equilibrium setting. Wealth effects, and their amplification in general equilibrium, explain a large fraction of the consumption and inflation response to changes in nominal interest rates in the standard equilibrium. In RANK, wealth effects are determined, generically, by the revaluation of public debt and the fiscal response to monetary policy. In a medium-scale DSGE model, we find a fiscal response that is several times larger than the response we estimate in the data. Therefore, the model is unable to generate sufficiently strong effects. In an analytical HANK model with positive private debt, private wealth effects amplify the response to monetary policy and improve the quantitative performance of the DSGE model.
An important paper on the important topic of distributional aspects of monetary policy.
February 12, 2020
By Jose Carreno
The United States has been experiencing a slowdown in productivity growth for more than a decade. I exploit geographic variation across U.S. Metropolitan Statistical Areas (MSAs) to investigate the link between the 2006-2012 decline in house prices (the housing bust) and the productivity slowdown. Instrumental variable estimates support a causal relationship between the housing bust and the productivity slowdown. The results imply that one standard deviation decline in house prices translates into an increment of the productivity gap — i.e. how much an MSA would have to grow to catch up with the trend — by 6.9p.p., where the average gap is 14.51%. Using a newly-constructed capital expenditures measure at the MSA level, I find that the long investment slump that came out of the Great Recession explains an important part of this effect. Next, I document that the housing bust led to the investment slump and, ultimately, the productivity slowdown, mostly through the collapse in consumption expenditures that followed the bust. Lastly, I construct a quantitative general equilibrium model that rationalizes these empirical findings, and find that the housing bust is behind roughly 50 percent of the productivity slowdown.
I used to think that productivity growth in the longer run is really tied to innovation. This paper challenges this view, as it shows that half of the productivity slowdown is tied to aggregate demand issues. Maybe there is still a link between aggregate demand and innovation, but this would be getting convoluted.
February 6, 2020
What Is Driving The TFP Slowdown? Insights From a Schumpeterian DSGE Model
By Marco Pinchetti
In this paper, I incorporate a Schumpeterian mechanism of creative destruction in a medium-scale DSGE framework. In the model, a sector of profit-maximizing innovators invests in R&D and endogenously generates productivity gains, ultimately determining the economy’s growth rate. I estimate the model using Bayesian methods on U.S. data of the last 25 years (1993q1-2018q4) in order to disentangle the key forces underlying the productivity slowdown experienced by the US economy since the early 2000s. In contrast with the previous literature, I exploit Fernald (2014) data on TFP, factor utilization and labour quality to discipline the production function, and find that the bulk of the TFP slowdown is due to a decrease in innovation’s ability to generate TFP gains. These findings challenge the view of a large part of the literature, according to which the recent TFP dynamics in the US are mostly driven by demand slumps and/or liquidity crunches.
Compositional nature of firm growth and aggregate fluctuations
By Vladimir Sirnyagin
This paper studies firm dynamics over the business cycle. I present evidence from the United Kingdom that more rapidly growing firms are born in expansions than in recessions. Using administrative records from Census data, I find that this observation also holds for the last four recessions in the United States. I also present suggestive evidence that financial frictions play an important role in determining the types of firms that are born at different stages of the business cycle. I then develop a general equilibrium model in which firms choose their managers’ span of control at birth. Firms that choose larger spans of control grow faster and eventually get to be larger, and in this sense have a larger target size. Financial frictions in the form of collateral constraints slow the rate at which firms reach their target size. It takes firms longer to get up to scale when collateral constraints tighten; therefore, businesses with the largest target size are affected disproportionately more. Thus, fewer entrepreneurs find it profitable to choose larger projects when financial conditions deteriorate. Using Bayesian methods, I estimate the model using micro and aggregate data from the United Kingdom. I find that financial shocks account for over 80% of fluctuations in the formation of businesses with a large target size, and TFP and labour wedge shocks account for the remaining 20%. An independently estimated version of the model with no choice over the span of control needs larger aggregate shocks in order to account for the same data series, suggesting that the intensive margin of business formation is important at business cycle frequencies. The model with the choice over the span of control generates an empirically relevant and non-targeted collapse in the right tail of the cumulative growth distribution among firms started in recessions, while the model without such a choice does not. The paper also discusses implications for micro-targeted government stimulus policies.
Two papers appearing in the same issue of the NEP-DGE report could look very promising if they were combined. Could we explain the productivity slow down by a change in the composition of innovating firms that now face more difficulties translating innovation?