Minimum Wage

"Minimum Wages and Employment: A Case Study of the Fast-Food Industry in New Jersey and Pennsylvania," by David Card and Alan B. Krueger. American Economic Review 84, no. 4 (September 1994): 772–793.

"The Economic Effects of Mandated Wage Floors," by David Neumark. Public Policy Institute of California Occasional Paper. February 2004.

"Minimum Wages and Employment: A Review of Evidence from the New Minimum Wage Research," by David Neumark and William Wascher. November 2006. NBER #12663.

"Minimum Wage Effects across State Borders: Estimates Using Contiguous Counties," by Arindrajit Dube, T. William Lester, and Michael Reich. Review of Economics and Statistics 92, no. 4 (November 2010): 945–964.

"Do Minimum Wages Really Reduce Teen Employment? Accounting for Heterogeneity and Selectivity in State Panel Data," by Sylvia A. Allegretto, Arindrajit Dube, and Michael Reich. Industrial Relations 50, no. 2 (April 2011): 205–240.

"Revisiting the Minimum Wage-Employment Debate: Throwing Out the Baby with the Bathwater?" by David Neumark, J. M. Ian Salas, and William Wascher. January 2013. NBER #18681.

"Effects of the Minimum Wage on Employment Dynamics," by Jonathan Meer and Jeremy West. August 2013. NBER #19262.

"Who Benefits from a Minimum Wage Increase?" by John W. Lopresti and Kevin J. Mumford. April 2015. SSRN #2590346.

The recent ruling by a New York State labor commission to increase the minimum wage for fast-food-chain workers to $15 an hour has revived interest in economists' conclusions about the employment effects of minimum wage increases. In this review I provide a summary of the papers I have found most useful.

Prior to 1992, the consensus was that an increase in the minimum wage reduces employment among those making between the old and new minimum levels. Research indicated that a 10 percent increase in the wage would reduce employment among affected workers by 1–3 percent.

In a series of papers published between 1992 and 1994, David Card and Alan Krueger (both of whom were then at Princeton University; Card is now at the University of California, Berkeley) explored the effect of an increase in the minimum wage in New Jersey on fast-food employment relative to neighboring Pennsylvania, whose minimum wage did not increase. They concluded that the increase did not reduce employment in New Jersey.

Two of the first stylized facts one learns in economics are that prices matter and the demand curves slope downward. Those facts mean that a legally mandated wage increase should result in less employment. So how could Card and Krueger have found no effect? In 2004, David Neumark (then at Michigan State University and now at the University of California, Irvine) argued that a combination of measurement error in the telephone survey used by Card and Krueger and the fact that the wages of many of the workers were already above both the new and old minimum wage accounted for their findings. Neumark also argued that for those workers who remained employed, the minimum wage is not a very effective anti-poverty instrument because only 20–30 percent of low-wage workers live in poor households. That is about the same percentage of minimum wage workers who live in households with incomes three times above the poverty level. And, ironically, the higher minimum wage reduces school and job training enrollment because workers can achieve higher wages with less schooling.

In 2006, Neumark and William Wascher (Federal Reserve) published a long review of the post-Card-and-Krueger minimum wage research and concluded that while some studies supported the findings of no employment effect, the longer and (in their view) methodologically better studies concluded that the combination of the Earned Income Tax Credit and increased minimum wage had very negative employment effects for minority teenagers. Because the price of their employment went up, employer demand for them decreased, while the pool of substitutes (predominantly older, low-skilled women) increased because of the EITC.

Subsequently, a 2010 paper by Arindrajit Dube (University of Massachusetts, Amherst), William Lester (University of North Carolina, Chapel Hill), and Michael Reich (Berkeley), and a 2011 paper by Sylvia Allegretto (Berkeley), Dube, and Reich argued that Neumark and Wascher's conclusions were flawed. According to the authors of these papers, Neumark and Wascher used inadequate statistical controls for what would have happened to employment if there had been no increase in the minimum wage. The 2010 paper compared restaurant employment in counties across state borders that had different minimum wages, and did not find any negative employment effects. The 2011 paper argued for the inclusion of regional or state employment trends over time so that the employment trend in a state with a minimum wage increase would be compared to the trend in a state without an increase. When those trends were included as control variables, the authors found no negative employment effects in states that increased their minimum wage.

In 2013, Neumark, Ian Salas (then a doctoral student at Cal-Irvine; now a postdoctoral fellow at Harvard University), and Wascher responded with a new analysis that included consideration of subtle but important econometric issues. The authors argued that the 2010 and 2011 papers failed to consider the effects of the early 1990s recession and the Great Recession on state employment time trends. The two recessions each altered the trend, but the 2010 and 2011 papers used linear trends. That means that their assumed "status quo" employment levels were, at various points of the business cycle, either above or below what a more careful assumption would have been. When the authors used a time trend that, they believe, more accurately represents the breaks and changes in the state-specific trends, the negative effect on teenage employment reappeared.

Neumark, Salas, and Wascher also took issue with the 2010 paper's assumption that adjacent counties divided by state borders are similar enough that one can conclude that a change in the minimum wage, rather than some other factor, is the cause of any observed employment differences. Said differently, the question is whether counties separated by state borders are more or less similar and thus that a search for correlation between minimum wage increases and restaurant employment requires fewer explicit control variables. Neumark, Salas, and Wascher estimate restaurant employment regressions for all counties and border counties and conclude that the prediction errors using border counties are worse than the prediction errors from randomly chosen counties. Thus border counties do not provide good controls.

A completely different response to the 2010 and 2011 papers is found in a 2013 working paper by Jonathan Meer (Texas A&M University) and Jeremy West (then a doctoral student at Texas A&M; now a postdoc at MIT). They argue that changes in minimum wages do not cause an abrupt change in employment levels. Instead, higher minimum wages change employment growth because employers do not adjust quickly to the new wage by cutting work hours; rather, they adjust slowly. Thus the dependent variable in minimum wage studies should be employment growth rather than employment levels. This implies that the use of state employment time trends as controls in the 2010 and 2011 papers automatically attenuates the effect of the wage on levels of employment toward zero. If the difference in wages between states lasts long enough, the effect on employment levels of a minimum wage increase eventually would be negative, but the real-world differences in wages across states are never large enough for a long enough time period, and thus the effect on employment levels is difficult to differentiate from no effect. But the effect on the rate of growth in employment is immediate and much easier to detect. Meer and West conclude that a real minimum wage increase of 10 percent reduces job growth by 0.3 percentage points annually, or about 15 percent of the baseline level.

The final study I review, by John Lopresti (College of William & Mary) and Kevin Mumford (Purdue University), uses responses in the Current Population Survey from the same individuals one year apart over the time period 2005–2008 and compares the wages of those in states that experienced minimum wage increases with the wages of those in states that did not increase their minimum wage. The increases varied from 10 cents to $2.10 an hour. Those in states whose minimum wage increased by 5 percent or less whose wages were below $11 an hour experienced a lower wage increase (11 percent less) than if they had lived in a state whose minimum wage did not increase. (On the other hand, those in states that increased the minimum wage by 10 percent or more and had initial wages within 20 percent of the minimum wage experienced more wage growth.) The authors' explanation is that small minimum wage increases serve as focal points around which employers can tacitly collude.

High-Frequency Trading

"The High-Frequency Trading Arms Race: Frequent Batch Auctions as a Market Design Response," by Eric Budish, Peter Cramton, and John Shim. March 2015. SSRN #2388265.

No development in financial markets causes more discussion and disagreement than high-frequency trading (HFT). Forty years ago, the "making" of a market in equities was done by "specialists" who owned seats on exchanges. They were compensated by the "spread"— the difference between the price they offered sellers and charged buyers. Those differences were large enough to more than cover costs. The excess profits were capitalized in the prices that specialists paid for the right to trade on an exchange.

Now liquidity is provided by traders using computers. In a previous column (Winter 2013–2014) I reported that many commentators view this change positively because the costs of trading have been dramatically reduced along with the rents to specialists. Bid-ask spreads have decreased over time and revenues to market-makers have decreased from 1.46 percent of traded face value in 1980 to just 0.11 percent in 2006. And HFT reduces stock price volatility. When the temporary ban on short sales of financial stocks existed in 2008, the financial stocks with the biggest decline in HFT had the biggest increase in volatility.

Those who emphasize the costs of HFT focus on the "arms race" among HFT participants to locate their servers closer and closer to the servers of electronic exchanges. This arms race exists because the transfer of buy and sell offers from any of the actual computerized exchanges to the National Market System (NMS) takes real time. This creates the possibility of learning about prices at a computerized exchange and trading on that information through the NMS before the NMS posts the information. Traders have responded to these facts by paying to locate their servers in the same location as exchange servers, utilizing the speed of light to arbitrage price differences at the level of thousandths of a second.

Budish and coauthors demonstrate that this arms race is the result of exchanges' use of "continuous-limit-order-book" design (that is, orders are taken continuously and placed when the asset reaches the order's stipulated price). They use actual trading data to show that the prices of two securities that track the S&P 500 are perfectly correlated at the level of hour and minute, but at the 10 and 1 millisecond level the correlation breaks down to provide for mechanical arbitrage opportunities even in a perfectly symmetrical information environment. The investment in speed has reduced the duration of the arbitrage opportunities, but not their existence or profitability. In a continuous auction design someone is always first. In contrast, in a "frequent batch" auction design (where trades are executed by auction at stipulated times that can be as little as a fraction of a second apart), the advantage of incremental speed improvements disappears. In order to end the arbitrage "arms race," the authors propose that exchanges switch to batch auctions conducted every tenth of a second.