February 2012, Vol. 135, No. 2
How businesses recruit
Trading with the Bear
Placing a value on playing the lottery
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The way individuals go about finding jobs has been researched heavily by economists, but the way businesses find suitable applicants to fill job openings hasn't received as much attention. In his article, "How Do Businesses Recruit?" (Business Review, Federal Reserve Bank of Philadelphia, fourth quarter 2011, http://www.philadelphiafed.org/research-and-data/publications/business-review/2011/q4/brq411_howdo-businesses-recruit.pdf), economist R. Jason Faberman provides insight into businesses' recruiting processes by analyzing data related to conditions, factors, and methods involved in the hiring process.
Using data from the Job Openings and Labor Turnover Survey (JOLTS) of the Bureau of Labor Statistics, Faberman and coresearchers Steven Davis and John Haltiwanger developed a vacancy yield measure that compares the hiring rate (hires as a percent of employment) to the vacancy rate (vacancies as a percent of employment plus vacancies) for major industries and regions of the United States. The vacancy yield helps measure how successful a firm is in its recruiting efforts. When the vacancy yield (the number of hires per vacancy posted) rises, a greater proportion of vacancies is filled in any given month. Vacancy yields were found to be highest in high-turnover industries, such as construction and retail trade, and lowest in health services, government, and information, industries with more formal recruiting practices. Geographically, the vacancy yield was found to be highest in the Midwest region and lowest in the Northeast. Disparities in vacancy yields can be attributed to firms' recruiting practices, job types, and growth rate.
Using a 1980 dataset from the Employment Opportunities Pilot Program and estimates replicated from research by John Barron, John Bishop, and William Dunkelberg, Faberman found that firms with more workers had higher average starting wages, interviewed more candidates for each position, and spent a greater number of hours recruiting, screening, and interviewing candidates. The average number of hours spent in these prehiring activities ranged from 6.2 hours per hire for small firms (those with one to nine workers) to 12.7 hours for firms with 251 or more workers. Likewise, the number of people that firms interviewed ranged from 5.2 to 8.3 and the starting wage (in 2009 dollars) ranged from $10.10 per hour to $13.00 per hour for firms with one to nine workers and firms with 251 or more workers, respectively.
There were also differences in hiring tendencies of employers based on the occupation that they were hiring for. The average length of vacancies for management positions was found to be 49.1 days, and for professional and technical occupations it was 37.1 days. In contrast, clerical jobs went vacant for 17.7 days, and personal and other services jobs were vacant an average of only 9.9 days. Interestingly, 29.4 percent of management positions were reported as being vacant for 0 days, meaning that no formal recruitment was necessary.
Faberman found that recruiting methods vary with the business cycle. His analysis of JOLTS data shows that both hiring and vacancies rise during economic expansions and contract during recessionary periods; the vacancy yield does the opposite because jobs are easily filled during downturns. Similarly, the job-filling rate—the proportion of vacancies filled on any given day—rises during recessions. Averaging 5.7 percent, the job-filling rate rose to 11 percent during the depths of the 1981–1982 recession and reached 8.6 percent during the most recent recession. When the job-filling rate rises, the escapefrom- unemployment rate falls because there are fewer open positions available. More recently, however, each trough in the escape-from-unemployment rate has been lower than the previous one, perhaps because of structural unemployment and other factors. Faberman concludes that economic models do well at capturing the friction and costs of matching workers to jobs but have more difficulty in accounting for the many ways in which businesses recruit workers for those jobs.
In anticipation of Russia's entry into the World Trade Organization (WTO), Daniel Griswold and Douglas Petersen present some of the main reasons they believe its entry into the WTO would be in the interest of the United States in their article, "Trading with the Bear: Why Russia's Entry into the WTO is in America's Interest" (Free Trade Bulletin no. 46, Center for Trade Policy Studies, CATO Institute, December 6, 2011, http://www.cato.org/pub_display.php?pub_id=13909).
Russia is currently the only member of the G-20, an international group of 19 countries with some of the largest industrial and emerging economies plus the European Union, that is outside the WTO. [Ten days after the CATO Institute article was published, Russia was officially invited to join the WTO; Russia has 6 months from that date to ratify its membership.] Because of the Jackson-Vanik amendment to the 1974 Trade Act, trade relations with communist countries that restrict the freedom of Jewish citizens and others to emigrate and that withhold other human rights were curtailed. The United States Congress passes a special trade exemption for Russia annually.
Griswold and Petersen contend that the Jackson-Vanik amendment is obsolete because migration from However, Russia now is unhindered. American access to Russia's underdeveloped market and the difficulty in eventually regaining the loss of market share caused by tariffs that currently put American exporters at a disadvantage are important reasons why Congress should grant permanent normal trade relations (PNTR) to the Russian Federation. The authors cite PNTR as a key to expanding U.S. exports into the Russian market.
By Congress not granting PNTR via repeal of the Jackson-Vanick amendment, the more than 150 other members of the WTO would have access to enhanced Russian market commitments while American producers would not. Russian demand for American goods and services represents a growing market. For instance, 66 million Russians were Internet users in 2010 and this number was projected to increase 20 percent in 2011. Everything from capital equipment and agricultural goods to technologies and advanced machinery are in demand.
Critics with objections to normalizing trade with Russia cite abuse of food safety regulations, Russian restrictions on international automobile trade, and a lack of adequate intellectual property rights protections as reasons not to grant unconditional most-favored-nation status as required by all WTO members. But the authors assert that the United States would be in a better position to protect its interests by use of WTO dispute settlement mechanisms.
Concern for human rights is also another obstacle, but Griswold and Peterson affirm that "some kind of compromise on human rights might become a necessary trade-off;" an option they suggest would be a bill mandating "asset freezes and/or travel bans for certain Russian individuals, particularly those involved in the murder of Sergei Magnitsky, a Russian lawyer who had recently unearthed tax fraud by the Russian government and then died while in custody."
The authors argue in their study that if Congress terminates the Jackson- Vanik amendment, President Obama will have the freedom to grant mostfavored- nation (MFN) status to Russia. Pursuing this policy "would yield immediate and tangible benefits for the American economy without sacrificing any vital foreign policy goals." Moreover, granting MFN status would be a gesture of goodwill, and by opening Russia to U.S. trade, Russia is likely to liberalize more quickly and deeply.
If you play the lottery, would you report 100 percent of your expenditures when surveyed? Have you ever thought how your gaming affects the national economy? Indeed, how do governments value the output of a lottery when estimating the gross domestic product (GDP)?
Economist Kam Yu uses an economics approach to study the Canadian lottery in "Measuring the Output and Prices of the Lottery Sector: An Application of Implicit Expected Utility Theory," a chapter in Price Index Concepts and Measurement, W. Erwin Diewert, John S. Greenless, and Charles R. Hulten, editors (University of Chicago Press: National Bureau of Economic Research, December 2009, http://www.nber.org/chapters/c5086.pdf).
Yu contends that the lottery is an important component of GDP and so an accurate way to measure the real output of the lottery is needed. The amount spent on the lottery is consistently underreported by households. Data from the Survey of Household Spending (SHS) show that 68.4 percent of families in Canada participate in lottery purchases, with an average expenditure per household of $238. However, lottery revenue reported by the government was 3 times more than the SHS figure. Yu proposes a direct utility approach to measure the value of government services related to lotteries.
The author investigated the economics of risk and uncertainty, noting that, "in the theory of consumption under uncertainty, the typical consumer is traditionally assumed to follow an optimal decision rule with risk-averse preferences. This leads to the well-known expected utility hypothesis (EUH) in which the degree of risk averseness is often assumed to be decreasing in wealth." The expected utility hypothesis implies that a risk-averse expected utility maximizer will never buy lottery tickets unless the payout is huge. The reality, as Yu points out, is that even risk-averse individuals purchase lottery tickets, and so EUH does not provide a reliable estimate of real output.
Yu instead applies implicit expected utility theory to measure lottery output. In doing so, he finds that the real output of the Canadian lottery is nearly three times higher than the official statistics, which use the total cost of providing the service in estimating the output. He asserts that an accurate estimate of the real output of the lottery also could be used to calculate an implicit price index that could serve as a deflator in the national accounts as well as a subindex in the consumer price index.
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