Has Wal-Mart Buried Mom and Pop?   2 comments

Does small business decline when Wal-Mart enters the market?

Many believe the mega discount store Wal-Mart is a plague set upon small “mom-and-pop” businesses.
The instant Wal-Mart moves into town, all small businesses are destroyed in its path, leaving  downtowns barren and empty. This popular misconception has garnered significant media publicity and widespread public acceptance. Former  President Clinton’s former secretary of labor, Robert B. Reich, wrote in a 2005 New York Times op-ed that Wal-Mart turns “main streets into ghost towns by sucking business away from small retailers.” One of the largest anti–Wal-Mart organizations, Wal-Mart Watch, released a report in 2005 claiming that a Wal-Mart expansion in Iowa was solely responsible for the extensive closings of mom-and-pop stores, including 555 grocery stores, 298 hardware stores, 293 building suppliers, 161 variety shops, 158 women’s stores, and 116 pharmacies.Are those claims true? In this article, we use rigorous econometric estimation techniques to examine the rate of self-employment and the number of small-employer establishments in communities where Wal-Mart has entered the market. We find that Wal-Mart has no statistically significant impact on the overall size of the small business sector in the United States. When all is said and done, there are just as many small businesses that are just as profitable despite the presence of Wal-Mart.

PREVIOUS ESTIMATION PROBLEMSThe oft-cited estimates of Wal-Mart’s alleged negative impact on small businesses, such as the Iowa example, are misleading  for several reasons. First, many of those estimates, found in a series of applied policy studies, lack formal econometric estimating procedures. The studies simply compare averages for
counties with Wal-Mart stores to those without Wal-Mart stores. Although the studies have attracted considerable media publicity, they are problematic and misleading because of the deficiency of econometric analysis, which makes it impossible to know whether the differences are statistically significant. Furthermore, without the use of control variables found in standard econometric analysis, the studies ignore the effects
of other economic and demographic factors that differ between counties with and without Wal-Mart stores.
The second problem with previous studies is that, as part of  the data for “small business,” they often lump in numbers from competing mega-retailers such as Kmart, Target, and Home Depot. Those retailers all suffer negative impacts as a result of  Wal-Mart’s entrance into the market. Given that flaw, it is uncertain to what extent the previous negative estimates can be used  to approximate the effect Wal-Mart has on true mom-and-pop businesses, as a Kmart’s store closing should not be counted in a true measure of the small business failure impact of Wal-Mart. The final two, and perhaps most noteworthy, problems with previous studies are
(1) they only use data for directly competing retail business sectors,
(2) they only evaluate those sectors within the specific county in which Wal-Mart opens, instead  of the store’s broader area.

Our research finds that a new Wal-Mart store results in both the immediate failure of some small businesses and the emergence of other small businesses — both in other sectors and in other counties. For example, if a new Wal-Mart store opens, causing a directly competing hardware store to close and subsequently a new antique boutique opens in its place, the previous studies would only observe the failure of the hardware store. Yet Wal-Mart saves consumers a significant amount of money that they can then spend on other goods and services, and we would expect this to result in more new business opportunities. For example, if the money saved by consumers creates a greater demand for recreational activity and, as a result, a whitewater rafting company opens in a neighboring county, this new business would not be accounted for in previous studies. We now consider this process in more detail
The previous research on Wal-Mart’s effects did not correctly model the welfare-enhancing process of “creative destruction.” Creative destruction occurs when the introduction of a new idea or product results in the obsolescence of other products. New inventions, for instance, often result in the business failures of products supplanted by now-outdated technologies.That is unfortunate for the old businesses, but it benefits
consumers and it frees money and resources that can then give rise to new businesses and further advancements. For instance, the locale of our university, Morgantown, W.Vais just one of many cities that have witnessed, first-hand, the process of creative destruction unleashed by Wal-Mart. Shortly after a new Wal-Mart store opened, Morgantown’s popular downtown area was wrought with empty storefronts. However, after only a brief period of time, the once-empty storefronts filled with new small businesses. A former women’s clothing shop transformed into a high-end restaurant. A former electronics store converted into an ice cream parlor. One by one, each of the vacant stores filled with new businesses, such as coffee shops, art galleries, and law firms. This process of creative destruction is able to increase economic efficiency by the reallocation of resources. Downtown retail space, which prior to a Wal-Mart store opening would be extremely competitive and allocated mainly to general merchandise stores, becomes an economically viable location for more elaborate types of small businesses once a Wal-Mart enters the area. Entrepreneurs who once could not afford the high rents of the limited downtown retail space are now granted an affordable opportunity to open their own businesses. It is also important to consider the money consumers save by purchasing goods at Wal-Mart’s lower prices. That money, which was previously spent on the same goods at more expensive mom-and-pop stores, can be reallocated to purchase specialty items in the boutique shops. Emek Basker of the University of Missouri–Columbia has found that the opening of a new Wal-Mart store results in city-wide price reductions of nearly two or three percent in the short run and approximately 10 percent in the long run. Consumers will spend at least some of that savings at other small businesses.
Because of its size, Wal-Mart’s impact is easily observed in U.S. aggregate-level data. As mentioned in the introduction, the Wal-Mart expansion in Iowa has been blamed for the closing of 1,581 total business firms. The data would imply a failure of 11.3 percent of all businesses in the state of Iowa. If computed as a percentage of only small businesses, Wal-Mart would be responsible for the failure of almost 30 percent of all Iowa small businesses. Have these immense declines in small business activity really occurred? If the answer to this question is yes, it will without a doubt be visible in aggregate data on U.S. small business activity. To begin an examination of the raw data, let us first view a comparison on the expansion of Wal-Mart stores and the rate of self-employment in the United States. The measurement of Wal-Mart stores includes both the chain’s traditional “discount stores” and its “supercenters,” while the rate of self-employment is calculated by taking nonfarm proprietor employment as a percentage of total nonfarm employment. Figure 1 provides this  comparison for the 48 continental U.S. states. As can be seen in Figure 1, over the time period in which the number of Wal-Mart stores dramatically increased from just a few to over 2,500, there was also a continual increase in the rate of  self employment.  This overall upward trend in self employment  is just as strong in the 1980s when Wal-Mart was rapidly expanding as it was in the 1970s. If the negative impact predicted by previous studies is correct, we should see a dramatic drop in self-employment. However, rather than a dramatic drop, the raw data suggest a nearly 50 percent increase in self-employment during the time frame.
A simple time-series regression confirms the relationship between Wal-Mart stores and selfemployment seen in Figure 1. After  controlling for basic factors such as per capita personal income and the unemployment rate, the regression results in a positive coefficient on Wal- Mart, contrary to the predictions of previous literature. To view those and other regression results not found in this article, please refer to our forthcoming publication in Economic Inquiry.  A second and third comparison of Wal-Mart stores to the number of establishments with one to four employees and the number of establishments with five to nine employees may also
be enlightening. This measurement of momand-pop businesses is defined by the number of retail establishments with one to four employees, or five to nine employees, per 100,000 of state population from the U.S. Census Bureau. However, the data are a bit more
complicated to use because the U.S. Census Bureau redefined the variable in 1998, causing a discontinuity. Unfortunately, the data also are not available for as many years as the self-employment data. Nonetheless, Figures 2a and 2b both demonstrate the same pattern. Although self-employment has been steadily increasing in the United States, the number of small establishments remains practically unchanged since 1985. Just by looking at the raw data, no evidence can be found to validate the arguments of previous Wal-Mart literature. Wal-Mart’s alleged negative effect on the small business sector simply cannot be found in the data. However, many factors can change over a 30-year time period. For example, mom-and-pop businesses may have developed Internet-based services that would make it easier to survive in the marketplace, thereby hiding the alleged negative effect of Wal-Mart. Because of such changes, a more rigorous cross-sectional analysis at a single year in time is necessary to draw a more firm, concise conclusion
on Wal-Mart’s true effect on the U.S. small business sector.
For the purpose of maximizing the number of control variables from the U.S. Census, our cross-sectional analysis uses data for the year 2000. For this analysis, both the level and growth of small business activity are examined.
RAW DATA To begin the cross-sectional analysis, it is also use

Posted December 5, 2011 by avinash2060 in Uncategorized

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