Starting in the early 1990s, countries in southern Europe experienced low productivity growth alongside declining real interest rates. We use data for manufacturing ﬁrms in Spain between 1999 and 2012 to document a signiﬁcant increase in the dispersion of the return to capital across ﬁrms, a stable dispersion of the return to labor, and a signiﬁcant increase in productivity losses from capital misallocation over time. We develop a model with size-dependent ﬁnancial frictions that is consistent with important aspects of ﬁrms’ behavior in production and balance sheet data. We illustrate how the decline in the real interest rate, often attributed to the euro convergence process, leads to a signiﬁcant decline in sectoral total factor productivity as capital inﬂows are misallocated toward ﬁrms that have higher net worth but are not necessarily more productive. We show that similar trends in dispersion and productivity losses are observed in Italy and Portugal but not in Germany, France, and Norway.
Randomness in individual discovery tends to spread out productivities in a population, while learning from others keeps productivities together. In combination, these two mechanisms for knowledge accumulation give rise to long-term growth and persistent income inequality. This paper considers a world in which those with more useful knowledge can teach those with less useful knowledge, with competitive markets assigning students to teachers. In equilibrium, students who are able to learn quickly are assigned to teachers with the most productive knowledge. The long-run growth rate of this economy is governed by the rate at which the fastest learners can learn. The income distribution reflects learning ability and serendipity, both in individual discovery and in the assignment of students to teachers. Because of naturally arising indeterminacies in this assignment, payoff irrelevant characteristics can be predictors of individual income growth. Ability rents can be large when fast learners are scarce, when the process of individual discovery is not too noisy, and when overhead labor costs are low.
In 1950 Mexico entered an economic takeoff and grew rapidly for more than 30 years. Growth stopped during the crises of 1982–1995, despite major reforms, including liberalization of foreign trade and investment. Since then growth has been modest. We analyze the economic history of Mexico 1877–2010. We conclude that the growth 1950–1981 was driven by urbanization, industrialization, and education and that Mexico would have grown even more rapidly if trade and investment had been liberalized sooner. If Mexico is to resume rapid growth — so that it can approach U.S. levels of income — it needs further reforms.
Prior to the mid-1980s, labor productivity growth was a useful barometer of the U.S. economy’s performance: it was low when the economy was depressed and high when it was booming. Since then, labor productivity has become significantly less procyclical. In the recent downturn of 2008–2009, labor productivity actually rose as GDP plummeted. These facts have motivated the development of new business cycle theories because the conventional view is that they are inconsistent with existing business cycle theory. In this paper, we analyze recent events with existing theory and find that the labor productivity puzzle is much less of a puzzle than previously thought. In light of these findings, we argue that policy agendas arising from new untested theories should be disregarded.
It is widely believed that an important factor underlying the rapid growth in China is increased foreign direct investment (FDI) and the transfer of foreign technology capital, which is accumulated know-how from investment in research and development (R&D), brands, and organizations that is not specific to a plant. In this paper, we study two channels through which FDI can contribute to upgrading of the stock of technology capital: knowledge spillovers and appropriation. Knowledge spillovers lead to new ideas that do not directly compete or devalue the foreign affiliate's stock. Appropriation, on the other hand, implies a redistribution of property rights over patents and trademarks; the gain to domestic companies comes at a loss to the multinational company (MNC). In this paper we build these sources of technology capital transfer into the framework developed by McGrattan and Prescott (2009, 2010) and introduce an endogenously-chosen intensity margin for operating technology capital in order to capture the trade-offs MNCs face when expanding their markets internationally. We first demonstrate that abstracting from technology capital transfers results in predicted bilateral FDI inflows to China that are grossly at odds with the data. We then use the bilateral inflows to parameterize the model with technology capital transfers and compute the global economic impact of Chinese policies that encouraged greater inflows of FDI and technology capital transfers. Microevidence on automobile patents is used to support our parameter choices and main findings.
Empirical studies quantifying the benefits of increased foreign direct investment (FDI) have been unable to provide conclusive evidence of a positive impact on the host country’s economic performance. I show that the lack of robust evidence is not inconsistent with theory, even if the gains to FDI openness are large. Anticipated welfare gains to increased inward FDI should lead to immediate declines in domestic investment and employment and eventual increases. Furthermore, since part of FDI is intangible investment that is expensed from company profits, gross domestic product (GDP) and gross national product (GNP) should decline during periods of abnormally high FDI investment. Using the model of McGrattan and Prescott (2009) and data from the IMF Balance of Payments to parameterize the time paths of FDI openness for each country in the sample, I do not find an economically significant relationship between the amount of inward FDI a country did over the period 1980—2005 and the growth in real GDP predicted by the model. This finding rests crucially on the fact that most of these countries are still in transition to FDI openness.
A framework is developed with what we call technology capital. A country is a measure of locations. Absent policy constraints, a firm owning a unit of technology capital can produce the composite output good using the unit of technology capital at as many locations as it chooses. But it can operate only one operation at a given location, so the number of locations is what constrains the number of units it operates using this unit of technology capital. If it has two units of technology capital, it can operate twice as many operations at every location. In this paper, aggregation is carried out and the aggregate production functions for the countries are derived. Our framework interacts well with the national accounts in the same way as does the neoclassical growth model. It also interacts well with the international accounts. There are constant returns to scale, and therefore no monopoly rents. Yet there are gains to being economically integrated. In the framework, a country’s openness is measured by the effect of its policies on the productivity of foreign operations. Our analysis indicates that there are large gains to this openness.
We estimate the effects of policy distortions on aggregate productivity. Based on a model of plant production and productivity uncertainty and heterogeneity, and using Chilean manufacturing data, we focus on the effect of taxation on the exit behavior of plants. We find that taxes do distort the liquidation decisions of firms, suggesting that policy distortions reduce the extent to which factors are reallocated towards the most productive plants. Our results have important consequences for growth and development, as policies that alter the measure of plants that operate in equilibrium change the short-run response of output to exogenous shocks and the long run level of aggregate TFP. In particular, we find that the amount of productivity lost due to excessive plant shutdowns are very large.