December 15, 2014
By Soojin Kim
Two key determinants of optimal tax policies in open economies are the mobility of factors of production, capital and labor; and strategic interaction between governments in setting their policies. This paper develops a two-country, open-economy model with labor mobility and a global financial market to study optimal taxation. Governments engage in tax competition in which they choose a labor income tax code and a capital income tax rate. A quantitative application of the model to the United Kingdom (UK) and Continental European countries (CE) shows that factor mobility and competition between governments are indeed crucial in the design of optimal policies. Incorporating labor mobility leads to a divergence in the optimal tax system: Unlike in an economy with only capital mobility, where both countries use similar capital income tax rates, the optimal capital income tax rate in the UK is lower than that in the CE when both capital and labor are mobile. This is due to the differences in productivity between the two countries. In the calibrated economy, the UK, whose productivity is higher than that of the CE, attracts more labor through migration. Thus, the welfare-maximizing level of capital in the relatively small CE is lower than that in the UK. Moreover, I find that capital income tax rates are higher with competition. With competition, both governments lower capital income tax rates, rendering the marginal benefit of a lower tax rate to decrease. The steady-state welfare gain from implementing the Nash equilibrium policies is about 11 percent of consumption of the status quo economy.
The optimal taxation literature largely assumes that the studied country lives in autarky. This is definitely not true, as tax competition is always on the mind of policy makers. The important message of this paper is that even with mobile factors and tax competition, there is room for tax rates to differ across countries, still giving each country some wiggle room to set its priorities.
December 9, 2014
By Simeon Alder, David Lagakos and Lee Ohanian
No region of the United States fared worse over the postwar period than the “Rust Belt,” the heavy manufacturing region bordering the Great Lakes. This paper hypothesizes that the Rust Belt declined in large part due to a lack of competitive pressure in its labor and output markets. We formalize this thesis in a two-region dynamic general equilibrium model, in which productivity growth and regional employment shares are determined by the extent of competition. Quantitatively, the model accounts for much of the large secular decline in the Rust Belt’s employment share before the 1980s, and the relative stabilization of the Rust Belt since then, as competitive pressure increased.
As a recent resident of the Rust Belt, I find this piece fascinating. Beyond the compelling examples about the lask of competition in the region, collusion among producers, high union power and the lack of technological progress, the paper has a nice model that shows how such inefficiencies could drag down the region. A lesson that could apply to other countries as well.
December 8, 2014
By Gonzalo Llosa, Lee Ohanian, Andrea Raffo and Richard Rogerson
We document large differences across OECD countries in fluctuations of the intensive and extensive margin of labor supply over the business cycle. Countries with larger fluctuations in employment relative to hours per worker tend to display larger fluctuations in total hours worked. These facts appear to be related to policies that impede the dismissal of workers. We then present a quantitative framework that features both margins of labor supply as well as costs to the adjustment of employment. Cross-country differences in dismissal costs can account for a large fraction of the patterns observed in the data.
Interesting analysis on a question I looked at without success in the late 1990’s, although then I focused on unionization. Nice dataset, too. Consistent hours data is difficult to obtain. The paper could, maybe, also address one puzzle I have had for a long time: why is output volatility so low in France? Given the huge labor market frictions there, it must be part of the story.
December 4, 2014
By Britta Kohlbrecher, Christian Merkl and Daniela Nordmeier
This paper shows analytically and numerically that there are two ways of generating an observationally equivalent comovement between matches, unemployment, and vacancies in dynamic labor market models: either by assuming a standard Cobb-Douglas contact function or by combining a degenerate contact function with idiosyncratic productivity shocks for new jobs. Despite this observational equivalence, we provide several reasons for why it is important to understand what happens inside the black box of job creation. We calibrate a combined model with both mechanisms to administrative German wage and labor market flow data. In contrast to the model without idiosyncratic shocks, the combined model is able to replicate the observed negative time trend in estimated matching functions. In addition, the full nonlinear combined model generates highly asymmetric business cycle responses to large aggregate shocks.
Matching functions are used a little bit blindly and indiscriminately, so it is useful to be reminded that they are really black boxes. If you use a matching function, you should understand what it assumes and implies. This paper shows nicely how we can think of matching function and where there specification matters or does not matter.
December 1, 2014
By Natalie Tiernan and Pedro gete
This paper is a quantitative study of two frictions that generate banks’ underinvestment in screening borrowers and, thus, overlending: 1) Limited liability, and 2) Banks failing to internalize that their credit decisions alter the pool of borrowers faced by other banks. The resulting lax lending standards overexpose banks to negative economic shocks and amplify the effects of economic fluctuations. They generate excessive volatility in credit, banks’ capital and output. We study a calibrated model whose predictions concerning the quantity and quality of credit are in line with recent U.S. business cycles. Quantitatively, limited liability is the friction that generates laxer lending standards. It induces 27% excess volatility in output relative to 8% from the other friction. Then we study three policy tools: capital requirements and taxes on banks’ lending and borrowings. The three tools encourage banks to screen more and should be state-contingent because the frictions vary with macroeconomic conditions. In quantitative terms, we find that taxes are better tools than capital requirements because they do not reduce credit going to the more productive agents.
Nice paper that shows that taxes, when uses judiciously, can have a beneficial impact in unexpected ways. While it is quite obvious that impose a tax reduce the level of that something, it is not clear it influences its volatility. It appears to be so efficient at this that it even counterweights the loss of loans in the average.
November 19, 2014
By Aleksander Berentsen, Samuel Huber and Alessandro Marchesiani
We investigate the positive and normative implications of a tax on financial market transactions in a dynamic general equilibrium model, where agents face idiosyncratic liquidity shocks and financial trading is essential. Our main finding is that agents’ portfolio choices display a pecuniary externality which results in too much trading. We calibrate the model to U.S. data and find an optimal tax rate of 2.5 percent. Imposing this tax reduces trading in financial markets by 30 percent.
It is difficult to think why a Tobin tax would make sense in a standard DSGE model. The paper above takes into account that people have two types of assets, liquid and illiquid ones. Naturally, they would like to minimize the amount of liquid assets they carry around as they typically have lower returns. The authors point out that having liquid assets provides, however, a positive externality onto the economy. One way to entice people to hold more of them is to make conversions between liquid and illiquid assets more costly, the Tobin tax. And the welfare benefit seems to be quite substantial.
November 18, 2014
By Kyle Herkenhoff
Unemployed households’ access to unsecured revolving credit (credit cards) nearly quadrupled from about 12 percent to about 45 percent over the last three decades. This paper analyzes how this large increase in revolving credit has impacted the business cycle. The paper develops a general equilibrium business cycle model with search in both the labor market and in the credit market. This generates a very rich and empirically plausible level of heterogeneity in work and credit histories while at the same time permitting a tractable model solution. Calibrating to the observed path of credit use between 1974 and 2012, I find that the large growth in credit access leads to deeper and longer recessions as well as moderately slower recoveries. Relative to an economy with credit fixed at 1970s levels, employment reaches its trough about 1 quarter later and remains depressed by up to .8 percentage points three years after the typical recession in this time period (e.g. employment is depressed by 2.8% rather than 2%). The mechanism is that when borrowing opportunities are easy to find, households optimally search for better-paying but harder-to-find jobs knowing that if the job search fails they can obtain credit to smooth consumption. Despite longer recessions and slower recoveries, increased credit card use enhances welfare by reducing consumption volatility and improving job-match quality.
It was seem at first counterintuitive that higher credit card debt, longer recession and more unemployment are welfare-enhancing, but it looks like matches are so much better in the search process that the outcome turns out to be better. And this despite the high credit card interest rates. This reminds me how entrepreneurship can be a driver for growth despite the high failure rate. As long as there is some mechanism in place that allows to capture at least some of the risk, taking risks is a good strategy.