Capital Income Taxation with Housing

January 27, 2020

By Makoto Nakajima

This paper quantitatively investigates capital income taxation in the general-equilibrium overlapping generations model with household heterogeneity and housing. Housing tax policy is found to affect how capital income should be taxed, due to substitution between housing and non-housing capital. Given the existing U.S. preferential tax treatment for owner-occupied housing, the optimal capital income tax rate is close to zero (1%), contrary to the high optimal capital income tax rate found with overlapping generations models without housing. A low capital income tax rate improves welfare by narrowing a tax wedge between housing and non-housing capital; the narrowed tax wedge indirectly nullifies the subsidies (taxes) for homeowners (renters) and corrects over-investment to housing. Naturally, when the preferential tax treatment for owner-occupied housing is eliminated, a high capital income tax rate improves welfare as in the model without housing.

The current debate about capital income (and wealth) taxes is neglecting an important dimension, as this paper nicely shows: how housing is taxed. This is especially important for international comparisons.

Two papers on Chinese Growth

January 20, 2020

Population Aging, Credit Market Frictions, and Chinese Economic Growth

By Michael Dotsey, Wenli Li and Fang Yang

We build a unified framework to quantitatively examine population aging and credit market frictions in contributing to Chinese economic growth between 1977 and 2014. We find that demographic changes together with endogenous human capital accumulation account for a large part of the rise in per capita output growth, especially after 2007, as well as some of the rise in savings. Credit policy changes initially alleviate the capital misallocation between private and public firms and lead to significant increases in both savings and output growth. Later, they distort capital allocation. While contributing to further increase in savings, the distortion slows down economic growth. Among factors that we consider, increased life expectancy and financial development in the form of reduced intermediation cost are the most important in driving the dynamics of savings and growth.

Deregulation as a Source of China’s Economic Growth

By Shiyuan Pan, Kai Xu and Kai Zhao

We develop a two-sector growth model of vertical structure in which the upstream sector features Cournot competition and produces intermediate goods that are used in the downstream sector for the production of final goods. In such a vertical structure, we show that deregulation and increased market competition in the upstream sector does not only increase its own productivity, but also has a substantial spillover effect on the productivity of the downstream sector through affecting factor prices. We calibrate the model to the Chinese economy and use the calibrated model to quantitatively evaluate the extent to which deregulation in the upstream market in China from 1998 to 2007 accounts for the rapid economic growth over the same period. Our quantitative experiments suggest that deregulation in the upstream market in China from 1998 to 2007 can account for a significant fraction of China’s economic growth during this period partly due to the significant spillover effect it has on the downstream sector. In addition, our model can also match several relevant observations in China during the same period including high and rising returns to capital, declining markups.

In this week’s crop of new papers on NEP-DGE, two on the same topic with seemingly very different explanations of Chinese growth. But as the papers individually note, the earlier growth is likely more due to deregulation (which has to stop at some point), while the later one is due to demographics. The demographic factor will become more interesting soon, as ageing plus stagnant or even declining population will put China in a similar situation to Japan.

The Unintended Consequences of Meritocratic Government Hiring

January 13, 2020

By Athanasios Geromichalos and Ioannis Kospentaris

In an attempt to mitigate the negative effects of clientelism, many governments around the world have adopted meritocratic hiring of public employees. This paper challenges the effectiveness of this common practice by showing that meritocratic government hiring can have unintended negative consequences on macroeconomic aggregates. In many countries, public employees enjoy considerable job security and generous compensation schemes; as a result, many talented workers choose to work for the public sector, which deprives the private sector of productive potential employees. This, in turn, reduces firms’ incentives to create jobs, increases unemployment, and lowers GDP. To quantify the effects of this novel channel, we extend the standard Diamond-Mortensen-Pissarides model to incorporate workers of heterogeneous productivity and a government that fills public sector jobs based on merit. We calibrate the model to aggregate data from Greece and perform a series of counterfactual exercises. We find that the adverse effects of our mechanism on the economy’s TFP, GDP, and unemployment are sizable.

The brightest minds will go where the best money is to be had. In a corrupt society, they will be the best at exploiting rents. They will go where the private gain is the highest. Is this where the social gain is the highest? If this is the case for the public sector, then I am fine with the perks of working there. The problem is that it has always been very difficult to measure this social gain, but it is obviously not high if you have a corrupt public sector.

I wonder, though whether the same reasoning could be applied to other sectors. For example in the United States, Wall Street has been attracting the best talent for years up to the Financial Crisis. Now it seems to be Silicon Valley. Are we better off now? Could one improve by attracting the best talent to the public sector?

Flexibility or certainty? The aggregate effects of casual jobs on labour markets

January 8, 2020

By Rachel Scarfe

There is much debate about the extent to which governments should regulate labour markets. One discussion concerns casual jobs, where firms do not need to guarantee workers certain, fixed, hours of work and instead “call-up” workers as and when needed. These jobs, sometimes known as “zero-hours”, “contingent” or “on-demand, provide flexibility for firms to change the size of their workforce cheaply and quickly and for workers to choose whether to supply labour in every period. This flexibility comes at the expense of certainty for both firms and workers. In this paper I develop a search and matching model incorporating casual jobs, which I use to evaluate the effect of labour market policies on aggregate outcomes. I find that a ban on casual jobs leads to higher unemployment, but also to higher production and aggregate worker utility. I also consider the effect of a higher minimum wage for casual jobs. I find that the effects are limited. These results are due to an offsetting mechanism: although higher wages lead to higher unemployment, as firms offer more full-time jobs, the number of workers actually called-up to work increases.

Interesting question, execution and results. The question now is how to deal with the trade-off between unemployment and production/utility when setting policy.