Seminar: The Economic Recovery and It’s Local Impact<br />Taggert J. Brooks, PhD<br />Associate Professor of Economics<br />University of Wisconsin-La Crosse<br />
Disclaimer:<br />I’ll pretend to know, but I probably don’t. The views expressed today might be my own, however they probably do not reflect the views of the sponsors, my employer, or my parents.<br />
Began late summer 2009<br />Expect it to be slow.<br />The Recovery<br />
The “problems” and their local impact <br />Health Care Reform<br />
Myth<br />Businesses are less competitive because of the burden of health care. <br />
National Compensation Measures as a Share of GDP, NIPA 1960-2006<br />Private Group Health Insurance<br />56.4% of GDP<br />56.3% of GDP<br />Other Fringe Benefits and Payroll Taxes<br />3.8%<br />6.7%<br />0.6%<br />4.1%<br />Wages<br />51.8%<br />45.6%<br />2006<br />Source: Kaiser Family Foundation analysis of data from the U.S. Department of Commerce, Bureau of Economic Analysis, National Income and Product Accounts, 1960-2006, Tables 1.1.5, 2.1, 6.11B, 6.11C, & 6.11D, 2008.<br />
Myth<br />Costs are rising more rapidly than other countries. <br />
Long Term Fiscal Problems<br />Medicare and Social Security. <br />
The recession lasted about 22 months, longest since 1929-1933 (43 months) but about as long as the 1980 and 1981 recessions combined.
We won’t know for sure the recovery is under way until well after it has begun. This is due in part to the delay with which we must deal when looking at the relevant data. This slide demonstrates that “search” data might provide us more immediate feedback on the state of the economy.
http://www.flickr.com/photos/jamesjordan/4120649726/sizes/o/Like the increased time it takes to find a match in the labor market it also takes longer to find a match in the marriage market.
In a previous post, I quoted economic historian Robert Fogel on the income elasticity of healthcare. Fogel's claim of an elasticity substantially greater than one brought this email from MIT's DaronAcemoglu: Dear Greg:We noticed your blog on health care and I thought it might be useful to bring my research with my colleague Amy Finkelstein and our PhD student Matt Notowidigdo to your attention.In this paper, Amy, Matt and I looked at the relationship between income and health care spending. Unlike the results you reference, our findings suggest that rising income cannot explain much of the rising share of GDP devoted to health spending. (In other words, we do not find evidence of an elasticity of health spending with respect to income that is greater than one). We think that the "assumed" relationship that health-care share of GDP should rise automatically as incomes rise is on much shakier grounds than most people realize.Of course, people with different priors will interpret the evidence differently, but we think in this case the evidence is interesting and informative. The paper is here.Of course, one may ask, if not income, what is responsible for the dramatic rise in the health-care share of GDP. Amy has a very interesting paper on this, which you may have seen, estimating that the spread of health insurance may have played quite a large role in explaining the rise in health spending. So our view has now evolved,as a result of the empirical evidence in these papers, to the tentative conclusion that much of the rise in the health-care share of GDP may be due to policies and regulations related to private and social insurance and the way that the health market is organized (that dreaded word "incentives"). But again I am sure many people will not agree with this conclusion.In any case, some quick reactions from us, which may or may not be useful to you.DaronThanks, Daron.Beyond a large income elasticity and the effects of incentives Daron describes, there is a third logical possibility to explain a rising healthcare share of GDP: an expansion in the range of products available to the consumer due to exogenous* technological change. As doctors figure out new and better ways to prolong and enhance life, we may rationally choose to buy these products. It might be tempting to view this effect as a large income elasticity (which is perhaps what Fogel is doing), for the technological change raises real incomes as well as healthcare spending. But the resulting parameter is not a true income elasticity, which measures how much more healthcare we buy if income rises while the range of products is held constant.--------*Of course, technological change is not completely exogenous. Surely, the incentives offered by such policies as the patent system and government research funding matter for medical advance. Here what I mean by "exogenous" is not driven primarily by the incentives determined by the health insurance system.
From : http://www.dwd.state.wi.us/oea/county_profiles/current/la_crosse_profile.pdfJobs and wages are the lifeblood of any economy. The more good-paying jobs in a region, the better the prospects for its economy; and the more diverse the county’s industry sectors, the more insulated it is from major losses. In La Crosse County, however, 28.4 percent of county jobs are in the industry super-sector of education & health; and another 21 percent are in the trade, transportation, & utilities super-sector. Within La Crosse County’s super-sector of trade, transportation, & utilities; wholesale trade comprises 22.1 percent of the jobs in this large grouping, retail trade comprises 61.7 percent, utilities comprises 1.2 percent and transportation & warehousing comprises 15.1 percent. As previously noted, employers in education and health services provide the greatest share of jobs in the county as well as the highest total payroll. Due to the number of postsecondary education institutions and specialized medical facilities that employ workers in highly-skilled occupations, the average annual wage in the industry super-sector of $39,845 is slightly higher than this industry’s average wage statewide. Employment in education and health care increased by more than 1,800 jobs in the last five years, dwarfing increases in other major industry sectors. This increase accounted for more than 85 percent of La Crosse County ‘s total increase in employment in the last five years . The annual average wages that an industry sector pays can depend upon many factors such as its geographic location, seasonal activity, the presence of workers under collective bargaining agreements, and others. But the most crucial wage structure component is an industry’ s occupationalcomposition. Even two companies in the same industry and the same county could show differing average wages if their occupational compositions are significantly different.
As much as 53 Trillion dollars. 34 trillion for medicare (of which about 8 trillion is prescription drugs) and the rest social security.