Patrick C. Higgins
Federal Reserve Bank of Atlanta
1000 Peachtree Street, N.E.
Atlanta, GA 30309-4470
Institutional Affiliation: Federal Reserve Bank of Atlanta
Information about this author at RePEc
NBER Working Papers and Publications
|April 2019||Did the 2017 Tax Reform Discriminate against Blue State Voters?|
with David Altig, Alan J. Auerbach, Darryl R. Koehler, Laurence J. Kotlikoff, Michael Leiseca, Ellyn Terry, Yifan Ye: w25770
The Tax Cut and Jobs Act of 2017 (TCJA) made significant changes to corporate and personal federal income taxation, including limiting the SALT (state and local property, income and sales taxes) deductibility to $10,000. States with high SALT tend to vote Democratic. This paper estimates the differential effect of the TCJA on red- and blue-state taxpayers and investigates the importance of the SALT limitation to this differential. We calculate the effect of permanent implementation of the TCJA on households using The Fiscal Analyzer: a life-cycle, consumption-smoothing program incorporating all major federal and state fiscal policies. We find that the average percentage increase in remaining lifetime spending under the TCJA is 1.6 percent in red states versus 1.3 percent in blue states. Am...
|September 2016||Impacts of Monetary Stimulus on Credit Allocation and the Macroeconomy: Evidence from China|
with Kaiji Chen, Haoyu Gao, Daniel F. Waggoner, Tao Zha: w22650
We construct a micro dataset that covers all newly originated bank loans by the 19 largest Chinese banks to individual firms and spans all sectors in the Chinese economy. We propose a two-stage framework comprised of a macro SVAR model and a dynamic panel model to estimate the average and aggregate effects of the 2009 monetary stimulus on the macroeconomy and credit allocation to SOEs and non-SOEs across key sectors. The two-stage framework is vital for obtaining the aggregate effects from the micro model. While credit expansion due to monetary stimulus favored the average SOE in manufacturing, non-SOEs enjoyed preferential credit treatment in real estate. There was no obvious favoritism of credit allocation toward the average SOE in infrastructure. In aggregate, non-SOEs are quantitative...
|July 2016||Forecasting China's Economic Growth and Inflation|
with Tao Zha, Karen Zhong: w22402
Although macroeconomic forecasting forms an integral part of the policymaking process, there has been a serious lack of rigorous and systematic research in the evaluation of out-of-sample model-based forecasts of China's real GDP growth and CPI inflation. This paper fills this research gap by providing a replicable forecasting model that beats a host of other competing models when measured by root mean square errors, especially over long-run forecast horizons. The model is shown to be capable of predicting turning points and to be usable for policy analysis under different scenarios. It predicts that China's future GDP growth will be of L-shape rather than U-shape.
Published: Patrick Higgins & Tao Zha & Wenna Zhong, 2016. "Forecasting China's economic growth and inflation," China Economic Review, . citation courtesy of