Robert Lucas’s famous critique of macro modeling focused the attention of modelers on what he called adaptive expectations: What’s happening “now” in a model’s data space is more important than what’s happened in the past. Lucas made us look at the margin, at the cutting edge of economic activity, and at how economic actors altered their economic behavior in the presence of major public policy changes. It is at the margin of economic activity that we find economic change. Models that fail to attend to the margin fail to contain any meaningful economics. Those that do, however, will discover a familiar actor inhabiting that margin, the same one who holds center stage in daily economic life: the creator of new value—the entrepreneur.
One of the many casualties of the Great Recession was the sanguine view among macroeconomists that they had pretty much succeeded in getting the microfoundations of their subject right. They believed they had a good handle on the relationship between central bank monetary policy and credit markets, between federal mortgage subsidties and the housing markets, and between tax policy and the supply channels for labor and capital.
Not so, of course: The major macroeconomic forecasting models failed to predict the Great Recession or even show more than a slowdown in output during the period 2008 through 2010. Today, the best of the macro modelers are rushing back to their microeconomics textbooks and empirical work to discover what they had overlooked.
Take, for example, labor supply elasticities. There is growing evidence that participation and supply elasticities with respect to tax policy changes may be grossly underestimated. Michael Keane’s excellent review essay in the December 2011 issue of the Journal of Economic Literature highlights a long list of problems with “consensus” supply elasticities that have prevailed for a very long time. These elasticities matter since low estimates suggest that raising taxes won’t matter much to labor decisions, thus encouraging policies that likely hurt macroeconomic performance and entrepreneurship.
And if something so fundamental as incorrect labor supply responses to tax policy are imbedded in our leading macro models, what should we suspect about capital supply responses or the assumed structure and rate of substitution of capital for labor? This list of things I’m worrying about is growing!
Capturing Entrepreneurial Activity
While we’re fretting over the growing shortcomings of traditional structural macro models, there’s something even more fundamentally wrong with macroeconomics that we need to underscore: With the exception of a few, very new agent-based models (one of which is at Heritage), no macro modeling system that I know of contains equations that attempt to capture entrepreneurial activity. We don’t even have macro models that attempt to estimate business formations as a substitute for entrepreneurship. Thus, no major model picks up the productivity of venture capital, the churn of successful/unsuccessful entrepreneurial activity, the relationship between prices and the pace of entrepreneurial activity, or the public policy effects on the entrepreneur.
If you believe, as I do, that marginal change in the pace of economic activity is defined in large part by the activities of entrepreneurs, then this deficiency becomes a major problem for macro modeling. If macroeconomics continues to exclude the role that entrepreneurship plays in setting the rate of change in overall economic activity, how can we ever hope that macroeconomists will produce forecasts that are significantly better than extrapolating the trend in population and capital growth? Surely, macroeconomics should be about deviations from trend as much as it is about trend and the potential of the economy.
That’s why the work of Zoltan Acs, Laszlo Szerb, and their colleagues at George Mason University and Terry Miller, Kim Holmes, Edwin Feulner, and their colleagues at The Heritage Foundation is so important. One of the main reasons we do not see entrepreneurship in economic models stems from the fact that we don’t know enough about how to connect entrepreneurial activity to the National Income and Product Accounts concepts and data that most models employ.
If you don’t believe this, just consider that the Bureau of Economic Analysis at the U.S. Department of Commerce just completed the satellite accounts to capture human capital investment, which is the first step toward a set of tables that will measure innovation. It was only in 2006 that the BEA received congressional funding for a portion of this innovation initiative, which principally will survey investment in people and new products—a far cry from the academic understanding of entrepreneurship but an undeniable first step in the right direction.
The Index of Economic Freedom (IEF) and the Global Entrepreneurship and Development Index (GEDI) are not only creating data that researchers can employ to better understand entrepreneurship, but also are reinforcing and advancing a research program that focuses on the institutional setting for entrepreneurial activity and the incentives that are associated with changes in the level of this key economic activity.
Importance of Empirical Testing
The data generated by these projects often are overlooked but, in my view, may be the most important long-term contribution of the IEF and the GEDI. In the end, nearly every economic theory needs to be subjected to empirical testing. (I exclude valuation theory that depends on unmeasurable, subjective assessments.) Indeed, the current standards in the economics profession strongly underscore this requirement. It is almost impossible to imagine advancement in economics without the ability of researchers to test theory and replicate research. Without data, little progress can be made in any branch of economics, particularly the fields of economic development.
Worse, the absence of data may be an excuse for some to plow ahead with erroneous economic policies, as we’ve seen in the economic development field. For example, an unwillingness to accept long-standing economic practices by international development agencies in some Sub-Saharan countries has led to disastrous economic dislocations over the past 60 years.
Those of us who have long been associated with the IEF know of hundreds of studies, some of them pathbreaking, that academics all over the world have produced using IEF data. Indeed, we take some small credit for the growing recognition that institutional factors matter enormously in whether an economy achieves its potential levels of output and income generation or not. It has been well known since at least the time of Adam Smith that institutional factors like the rule of law matter to economic growth. Empirically assessing the significance of these factors, however, is a rather recent enterprise. Robert Barro’s book, The Determinants of Economic Growth, is a good example of this line of research.
The development of data also has supported the growing research program on how entrepreneurial activity languishes or flourishes within varying public policy regimes. The 2012 GEDI and the IEF bring a great deal of this research to light and contribute enormous insights to the configuration of policies and incentives that lead to robust entrepreneurship. I’m particularly happy to see the number of connections made in this year’s edition to the slump in economic activity. If these connections between the institutional and individual factors continue to provide insight into the pace of entrepreneurial activity when good economic times return, then we have the makings of strong linkages to macroeconomic concepts.
Looking at the Margin
These considerations lead me back to macroeconomic modeling. Robert Lucas’s famous critique of macro modeling focused the attention of modelers on what Lucas called adaptive expectations. That is, what’s happening “now” in a model’s data space is more important than what’s happened in the past. Lucas made us look at the margin, at the cutting edge of economic activity, and at how economic actors altered their economic behavior in the presence of major public policy changes.
If we carry his insights forward, we will see our research program on entrepreneurship and the general economy. It is at the margin of economic activity that we find economic change. Models that fail to attend to the margin fail to contain any meaningful economics. Those that do, however, will discover a familiar actor inhabiting that margin, the same one who holds center stage in each of these indexes: the creator of new value—the entrepreneur.
—William W. Beach is John M. Olin Senior Fellow in Economics and Director of the Center for Data Analysis at The Heritage Foundation. These remarks were delivered at the launch of the 2012 Global Entrepreneurship and Development Index in Washington, D.C
Michael P. Keane, “Labor Supply and Taxes: A Survey,” Journal of Economic Literature, Vol. 49, No. 4 (December 2011), pp. 961–1075.
Acs and Szerb are the main editors of The 2012 Global Entrepreneurship and Development Index (Northampton, Mass.: Edward Elgar Publishing Limited, 2012). Miller, Holmes, and Feulner are the principal editors of the 2012 Index of Economic Freedom (Washington, D.C.: The Heritage Foundation and Dow Jones & Company, Inc., 2012).
Robert Barro, The Determinants of Economic Growth: A Cross-Country Empirical Study (Boston, Mass.: MIT Press, 1997).
Robert E. Lucas, Jr., “Econometric Policy Evaluation: A Critique,” Carnegie-Rochester Conference Series on Public Policy, Vol. 1, Issue 1 (1976), pp. 19–46.