Research Database

In this paper, we extend the growth model to include firm-specific technology capital and use it to assess the gains from opening to foreign direct investment. A firm’s technology capital is its unique know-how from investing in research and development, brands, and organization capital. Technology capital is distinguished from other forms of capital in that a firm can use it simultaneously in multiple domestic and foreign locations. A country can exploit foreign technology capital by permitting direct investment by foreign multinationals. In both steady-state and transitional analyses, the extended growth model predicts large gains to being open.

We analyze the setting of monetary and nonmonetary policies in monetary unions. We show that in these unions a time inconsistency problem in monetary policy leads to a novel type of free-rider problem in the setting of nonmonetary policies, such as labor market policy, fiscal policy, and bank regulation. The free-rider problem leads the union’s members to pursue lax nonmonetary policies that induce the monetary authority to generate high inflation. The free-rider problem can be mitigated by imposing constraints on the nonmonetary policies, like unionwide rules on labor market policy, debt constraints on members’ fiscal policy, and unionwide regulation of banks. When there is no time inconsistency problem, there is no free-rider problem, and constraints on nonmonetary policies are unnecessary and possibly harmful.

Arrow (1962) argued that since a monopoly restricts output relative to a competitive industry, it would be less willing to pay a fixed cost to adopt a new technology. Arrow’s idea has been challenged and critiques have shown that under different assumptions, increases in competition lead to less innovation. We develop a new theory of why a monopolistic industry innovates less than a competitive industry. The key is that firms often face major problems in integrating new technologies. In some cases, upon adoption of technology, firms must temporarily reduce output. We call such problems switchover disruptions. If firms face switchover disruptions, then a cost of adoption is the forgone rents on the sales of lost or delayed production, and these opportunity costs are larger the higher the price on those lost units. In particular, with greater monopoly power, the greater the forgone rents. This idea has significant consequences since if we add switchover disruptions to standard models, then the critiques of Arrow lose their force: competition again leads to greater adoption. In addition, we show that our model helps explain the accumulating evidence that competition leads to greater adoption (whereas the standard models cannot).

Three of the arguments made by Temin (2008) in his review of Great Depressions of the Twentieth Century are demonstrably wrong: that the treatment of the data in the volume is cursory; that the definition of great depressions is too general and, in particular, groups slow growth experiences in Latin America in the 1980s with far more severe great depressions in Europe in the 1930s; and that the book is an advertisement for the real business cycle methodology. Without these three arguments — which are the results of obvious conceptual and arithmetical errors, including copying the wrong column of data from a source — his review says little more than that he does not think it appropriate to apply our dynamic general equilibrium methodology to the study of great depressions, and he does not like the conclusion that we draw: that a successful model of a great depression needs to be able to account for the effects of government policy on productivity.

There is much debate about the usefulness of the neoclassical growth model for assessing the macroeconomic impact of fiscal shocks. We test the theory using data from World War II, which is by far the largest fiscal shock in the history of the United States. We take observed changes in fiscal policy during the war as inputs into a parameterized, dynamic general equilibrium model and compare the values of all variables in the model to the actual values of these variables in the data. Our main finding is that the theory quantitatively accounts for macroeconomic activity during this big fiscal shock.