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Author:Hong, Jay H. 

Working Paper
On the employment effect of technology : evidence from U.S. manufacturing for 1958-1996

Recently, Gal and others have found that technological progress may be contractionary: a favorable technology shock reduces hours worked in the short run. We ask whether this observation is robust in disaggregate data. According to our VAR analysis of 458 four-digit U.S. manufacturing industries for 1958-1996, some industries do exhibit temporary reduction in hours in response to a permanent increase in TFP. However, there are far more industries in which technological progress significantly increases hours. Using micro data on average price duration, we ask whether the difference across ...
Working Paper , Paper 03-06

Working Paper
Life insurance and household consumption.

In this paper, we use data of life insurance holdings by age, sex, and marital status to infer how individuals value consumption in different demographic stages. Essentially, we use revealed preference to estimate equivalence scales and altruism simultaneously in the context of a fully specified model with agents facing U.S. demographic features and with access to savings markets and life insurance markets. Our findings indicate that individuals are very caring for their dependents, that there are large economies of scale in consumption, that children are costly but wives with children ...
Working Papers , Paper 04-10

Working Paper
Do technological improvements in the manufacturing sector raise or lower employment?

We find that technology's effect on employment varies greatly across manufacturing industries. Some industries exhibit a temporary reduction in employment in response to a permanent increase in TFP, whereas far more industries exhibit an employment increase in response to a permanent TFP shock. This raises serious questions about existing work that finds that a labor productivity shock has a strong negative effect on employment. There are tantalizing and interesting differences between TFP and labor productivity. We argue that TFP is a more natural measure of technology because labor ...
Working Paper , Paper 05-02

Working Paper
Do technological improvements in the manufacturing sector raise or lower employment?

We find that technology's effect on employment varies greatly across manufacturing industries. Some industries exhibit a temporary reduction in employment in response to a permanent increase in TFP, whereas far more industries exhibit an employment increase in response to a permanent TFP shock. This raises serious questions about existing work that finds that a labor productivity shock has a strong negative effect on employment. There are tantalizing and interesting differences between TFP and labor productivity. We argue that TFP is a more natural measure of technology because labor ...
Working Papers , Paper 05-5

Working Paper
Labor-Market Uncertainty and Portfolio Choice Puzzles

The standard theory of household-portfolio choice is hard to reconcile with the following facts: (i) Households hold a small amount of equity despite the higher average rate of return. (ii) The share of risky assets increases with the age of the household. (iii) The share of risky assets is disproportionately larger for richer households. We develop a life-cycle model with age-dependent unemployment risk and gradual learning about the income profile that can address all three puzzles. Young workers, on average asset poor, face larger labor-market uncertainty because of high unemployment risk ...
Working Paper , Paper 14-13

Working Paper
Income Volatility and Portfolio Choices

Based on administrative data from Statistics Norway, we find economically significant shifts in households' financial portfolios around structural breaks in income volatility. When the standard deviation of labor-income growth doubles, the share of risky assets decreases by 4 percentage points. We ask whether this estimated marginal effect is consistent with a standard model of portfolio choice with idiosyncratic volatility shocks. The standard model generates a much more aggressive portfolio response than we see in the data. We show that Bayesian learning about the underlying volatility ...
Working Paper , Paper 20-01

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