Research Database

This paper illustrates how to use instrumental variables procedures to estimate the parameters of a linear rational expectations model. These procedures are appropriate when disturbances are serially correlated and the instrumental variables are not exogenous.

A unified growth theory is developed that accounts for the roughly constant living standards displayed by world economies prior to 1800 as well as the growing living standards exhibited by modern industrial economies. Our theory also explains the industrial revolution, which is the transition from an era when per capita incomes are stagnant to one with sustained growth. We use a standard growth model with one good and two available technologies. The first, denoted the Malthus technology, requires land, labor, and reproducible capital as inputs. The second, denoted the Solow technology, does not require land. We show that in the early stages of development, only the Malthus technology is used, and, due to population growth, living standards are stagnant despite technological progress. Eventually, technological progress causes the Solow technology to become profitable, and both technologies are employed. In the limit, the economy behaves like a standard Solow growth model.

We explore monetary policy in a world without currency. In our world, money is a form of government debt that bears interest, which can be negative as well as positive. Services of money are a factor of production. We show that the national accounts must be revised in this world. Using our baseline economy, we determine the balanced growth paths for a set of money interest rate target policy regimes. Besides this interest rate, the only policy variable that differs across regimes is either the labor income tax rate or the inflation rate. We find that Friedman monetary satiation without deflation is possible. We also examine a set of inflation rate targeting regimes. Here, the only other policy variable that differs across policy regimes is the tax rate. There is a sequence of markets with outcome in each market being a Debreu valuation equilibrium, which determines the vector of assets and liabilities households take into the subsequent period. Evaluating a policy regime is an advanced exercise in public finance. Monetary satiation is not optimal even though money is costless to produce. A preliminary version of this paper circulated under the title “Monetary Policy with 100 Percent Reserve Banking: An Exploration.”

Although the role of financial constraints on entrepreneurial choices has received considerable attention, the effects of these constraints on aggregate capital accumulation and wealth inequality are less known. Entrepreneurship is an important determinant of capital accumulation and wealth concentration and, conversely, the distribution of wealth affects entrepreneurial choices in the presence of borrowing constraints. We construct a model that matches wealth inequality very well, for both entrepreneurs and non-entrepreneurs, and find that more restrictive borrowing constraints generate less wealth concentration, but also reduce average firm size, aggregate capital, and the fraction of entrepreneurs. We also find that voluntary bequests are an important channel that allows some high-ability workers to establish or enlarge an entrepreneurial activity: with accidental bequests only, there would be fewer large firms, fewer entrepreneurs, and less aggregate capital, but also less wealth concentration.

In this paper, we build a model of the transition following large-scale economic reforms that predicts both a substantial drop in output and a prolonged pause in physical investment as the initial phase of the optimal transition following the reform. We model reform as a change in policy which induces agents to close existing enterprises using old technologies of production and to open up new enterprises adopting new technologies of production. The central idea of our paper is that it is costly to close old enterprises and open new enterprises because, in doing so, information capital built up about old enterprises is lost and time must pass before information capital about new enterprises can be acquired. Thus, an acceleration of the pace of industry evolution leads in the short run to a net loss of information capital, a drop in productivity, a recession, and a fall in physical investment. We calibrate our model of industry evolution, information capital, and transition to match micro data on industry evolution in the United States and macro data from the United States, Japan, and the former communist countries of Europe. We find that the loss of information capital that accompanies a major acceleration in the pace of industry evolution in an economy leads initially to a decade of recession and a five year pause in physical investment before the benefits of reform are realized.

This paper reviews selected studies in the theory of macroeconomic stabilization policy and summarizes their key findings. A simple model is constructed which includes all surveyed models as special cases. All solutions are derived and described step by step.

In the 1970s, U.S. asset markets witnessed (i) a 25% dip in the ratio of aggregate household wealth relative to GDP and (ii) negative comovement of house and stock prices that drove a 20% portfolio shift out of equity into real estate. This study uses an overlapping generations model with uninsurable nominal risk to quantify the role of structural change in these events. We attribute the dip in wealth to the entry of baby boomers into asset markets, and to the erosion of bond portfolios by surprise inflation, both of which lowered the overall propensity to save. We also show that the Great Inflation led to a portfolio shift by making housing more attractive than equity. Apart from tax effects, a new channel is that disagreement about inflation across age groups drives up collateral prices when credit is nominal.

This paper is an extension of Monika Piazzesi's and Martin Schneider's work while they were in the Research Department of the Federal Reserve Bank of Minneapolis.

Our objective is to understand how fundamental uncertainty can affect the long-run growth rate and what factors determine the nature of the relationship. Qualitatively, we show that the relationship between volatility in fundamentals and policies and mean growth can be either positive or negative. We identify the curvature of the utility function as a key parameter that determines the sign of the relationship. Quantitatively, we find that when we move from a world of perfect certainty to one with uncertainty that resembles the average uncertainty in a large sample of countries, growth rates increase, but not enough to account for the large differences in mean growth rates observed in the data. However, we find that differences in the curvature of preferences have substantial effects on the estimated variability of stationary objects like the consumption/output ratio and hours worked.

Trade protection remains a prominent feature of the current world economy and likely has significant effects on industries and macroeconomies. In this paper a particular type of policy, price supports, is analyzed in a two-country, dynamic, general equilibrium model. This model brings new perspectives to the analysis in that it is monetary and has labor mobility within countries between the traded-goods and non–traded-goods sectors. It is found that: (1) The introduction of price supports in an economy benefits only the agents currently working in the traded-goods sector. (2) Cooperation among countries in setting policies results in a higher level of price supports than does noncooperation. (3) Price-support policies can importantly affect the transmission of monetary policy effects, introducing permanent changes in real variables where there were none before and even reversing the signs of changes in some variables.

To understand how best to combat COVID-19, we must understand how deadly is the disease. There is a substantial debate in the epidemiological literature as to whether the fatality rate is 1% or 0.1% or somewhere in between. In this note, I use an SIR model to examine why it is difficult to estimate the fatality rate from the disease and how long we might have to wait to resolve this question absent a large-scale randomized testing program. I focus on uncertainty over the joint distribution of the fatality rate and the initial number of active cases at the start of the epidemic around January 15, 2020. I show how the model with a high initial number of active cases and a low fatality rate gives the same predictions for the evolution of the number of deaths in the early stages of the pandemic as the same model with a low initial number of active cases and a high fatality rate. The problem of distinguishing these two parameterizations of the model becomes more severe in the presence of effective mitigation measures. As discussed by many, this uncertainty could be resolved now with large-scale randomized testing.