The Health Care Industry and La Crosse County
The Health Care Industry and La Crosse County
THE HEALTH CARE INDUSTRY AND LA CROSSE COUNTY: Mary Meehan‐Strub Professor, Department of Family Development Family Living Agent La Crosse County UW‐Extension mary.meehan‐email@example.com Steven Deller Professor, Department of Agricultural and Applied Economics Community Economic Development Specialist University of Wisconsin‐Madison/Extension firstname.lastname@example.org Karl Green Associate Professor, Department of Community Resource Development Community Resource Development Educator La Crosse County UW‐Extension email@example.com January 2012 Issued in furtherance of Cooperative Extension work, Acts of May 8, and June 30, 1914, in cooperation with the U.S.
Department of Agriculture. Rick Klemme, Cooperative Extension, University of Wisconsin‐Extension. University of Wisconsin‐Extension, U.S. Department of Agriculture and Wisconsin counties cooperating. UW‐Extension provides equal opportunities in employment and programming, including Title IX and ADA. The Health Care Industry and La Crosse County: Will Medicaid and BadgerCare Budget Reduction Impact the Local Economy?
1 The Health Care Industry and La Crosse County: Will Medicaid and BadgerCare Budget Reductions Impact the Local Economy?1 Mary Meehan‐Strub, Steven Deller and Karl Green Executive Summary With rising health care costs and rapidly expanding Medicaid and BadgerCare enrollment the State of Wisconsin is facing significant budget deficits in these programs. The Walker Administration has proposed a total of about $554 million in Medicaid cuts to address these significant budget shortfalls. The changes sought may result in 65,000 poor adults and children leaving state health insurance programs because they would no longer be eligible or able to afford coverage.
While it is unclear how the federal government will respond to the Wisconsin proposals, it is clear that the flow of Medicaid and BadgerCare funds into La Crosse County will be reduced. To help local officials and concerned citizens of La Crosse County think through the potential impacts of these program cuts we explore the importance of the health care sector to the County economy. This report has three main parts: (1) a broad discussion of the County economy over time with a focus on the health care industry, (2) the contribution of the health industry to the County economy, and (3) the potential economic impacts of reductions in Medicaid and BadgerCare reimbursements.
The latter part of the analysis provided in this report is the most difficult to undertake because it is not clear what those reductions might be or how hospitals, medical clinics and other health care providers will respond to these proposed cuts. Because Medicaid reimbursement rates are significantly below cost of services, health care providers lose money by accepting Medicaid patients. In addition to the ripple effect cuts to Medicaid & BadgerCare will create, these cuts do not necessarily eliminate the expenditures or the need for expenditures. The cost of these expenditures shifts from the federal and state government to local (La Crosse County) health care providers and health care clients.
The extent to how much cost‐shifting occurs, whether hospitals pick up 100% of the cost shifting, hold their business entity harmless and pass the cost on to patients, or a combination of these, is unknown. Hospital administrators may have concern with this type of analysis, as hospitals must maintain a base or minimum number of staff regardless of their patient bed census. This dynamic makes an assessment of the economic impact of a reduction in Medicaid payments difficult.
As a result of this dynamic, the third part of the analysis presented in this report should be viewed as a starting point for further community discussions about the economic impacts of reduced Medicaid and BadgerCare funding on the business community as well as the health care industry‐‐a dominant economic force within La Crosse County, the impact on health care needs for individuals and families affected by the reduction, to ultimately come up with better solutions. 1 The report has benefited from the helpful comments of Lorie Graff‐ Economic Support Manager, Jason Witt‐ La Crosse County Human Services Director, Dean Ruppert‐ Operations Administrator, with La Crosse County Human Services.
2 Introduction With rising health care costs and rapidly expanding Medicaid and BadgerCare enrollment the State of Wisconsin is facing significant budget deficits in these programs. The Walker Administration has proposed a total of about $554 million in Medicaid cuts to address these significant budget shortfalls. The changes sought may result in 65,000 poor adults and children leaving state health insurance programs because they would no longer be eligible or able to afford coverage. While it is unclear how the federal government will respond to the Wisconsin proposals, it is clear that the flow of Medicaid and BadgerCare funds into La Crosse County will be reduced.
To help local officials and concerned citizens of La Crosse County think through the potential impacts of these program cuts we explore the importance of the health care sector to the County economy. This report has three main parts: (1) a broad discussion of the County economy over time with a focus on the health care industry, (2) the contribution of the health industry to the County economy, and (3) the potential economic impacts of reductions in Medicaid and BadgerCare reimbursements. The latter part of the analysis provided in this report is the most difficult to undertake because it is not clear what those reductions might be or how hospitals, medical clinics and other health care providers will respond to these proposed cuts.
Because Medicaid reimbursement rates are significantly below cost of services, health care providers lose money by accepting Medicaid patients. This dynamic makes an assessment of the economic impact of a reduction in Medicaid payments difficult. As a result of this dynamic the third part of the analysis presented in this report should be viewed as a starting point for further discussion.
General County Economic Trends There are several ways to measure the growth of the local economy ranging from population and employment to income levels, among others. La Crosse County has experienced stable population growth and for the past 30 years has largely paralleled the population growth of Wisconsin (Figure 1). For the most recent few years, however, the population growth of La Crosse County has accelerated slightly. Upon closer examination it appears that from 2003 to 2006 there was a slow‐down in the growth rate and the most recent time period has returned to the longer‐term growth trends.
Note that for the past 20 years the growth for La Crosse County has lagged behind the growth rate for the U.S. Not surprising, much of the U.S. population *See Resources (Page 10) *See Resources (Page 10)
3 growth has occurred in warmer climate southern states such as Florida and Texas. Naturally, as the population of La Crosse County and the surrounding area grows the demand for health care services will also grow. Over the whole of the time period examined (1969‐2009) employment has grown strongly in La Crosse County outpacing not only the employment growth rate of Wisconsin but also the growth rate of the U.S. (Figure 2). The downturn in employment during the recent “Great Recession” is clearly evident at the end of the time period examined. When growth in population, which was a little over 40 percent from 1969 to 2009, is compared to growth in employment, which is about 130 percent over the same time period, it is clear that job growth far outpaces population growth.
This difference in population and employment growth can be readily seen by examining the population: employment ratio which is simply the number of people in the community for each job (Figure 3). In 1969 there were about 2.2 people for every job, but over time that ratio has declined significantly. In 2009, the ratio is about 1.4 people for every job in La Crosse County. This represents a 34.4 percent decline in the ratio. Also note how the population: employment ratio for the County is consistently below either the national or state average. This can easily be explained by the fact that La Crosse County, and in particular, the City of La Crosse and the immediately surround communities such as Onalaska, serves as a regional hub for retail and services (e.g., health care, financial, education, transportation).
The large differences in population and employment growth, best reflected in the population: employment ratio can be explained by two concurrent trends. First, much of the job growth has been in the form of part‐time employment opportunities. This is reflected in the strong job growth in retail and personal services. It also is reflected in the growing size of the “working class” which speaks to the growing number of persons who are working multiple part‐time jobs. The larger question this raises is if these jobs can provide sustainable growth. The second concurrent trend helping understand the patterns in Figure 3 is the significant increase in the labor force participation rate for women.
In 1969 the women labor force participation rate was about 42.7 and in 2009 the rate increased to 59.2 percent. This significant increase in women in the labor force provided the pool of labor to fill many of those increasing jobs. This growth peaked, however, in 1999 at 60.0 percent. This peaking of the growth in the women labor force participation rate raises the question of who will fill the jobs as the economy grows. *See Resources (Page 10) *See Resources (Page 10)
4 *See Resources (Page 10) More important to this study is the job growth in the health care sector. Unfortunately, the annual data at our disposal for these long‐term analyses aggregates health care and social services (NAICS Code 62). In addition to including traditional health care industries such as hospitals, medical clinics, dentist offices and resident care facilities it also includes individual and family services, community relief services (e.g., food banks, emergency housing, etc.) and day care centers. It is clear, that for La Crosse County this category is dominated by traditional health care services.
Total employment growth over 1969 to 2009 for La Crosse County was about 130 percent (Figure 3) but for the health care sector employment growth for the County was just over 390 percent (Figure 4) . This growth in La Crosse County health care employment outpaces both Wisconsin (about 280 percent) and the U.S. (also about 280 percent). More remarkable the rate of growth in health care employment in La Crosse County appears to be accelerating in the growth rate. This increase is a reflection of the overall growth in the health care sector for both the U.S. and Wisconsin. As we age as a society and income grows the demand for health care services will continue to grow and this is reflected in the very strong employment growth.
Second, as identified in a recent Wisconsin Hospitals Association (WHA) study by Deller (2011) La Crosse County has the highest level of dependency on hospitals for economic activity compared to all other Wisconsin counties.2 The strong growth in health care employment coupled with the results of the WHA study one could reasonably conclude that the health care sector is a “cluster” industry for the County. Here clusters are concentrations of interconnected industries that create what economists call “agglomeration economies” or “external economies of scale.” The strength of the industry cluster creates an environment where the industry feeds off itself and grows more rapidly.
(See Appendix A for a more detailed discussion of La Crosse County Clusters.) The current unemployment situation and the slow recovery from the “Great Recession” has made job growth the focal point of nearly all economic growth and development policy discussions. But increasingly the quality of the jobs including wage and salary pay levels has become an equally important element. If we examine the inflation adjusted (i.e., real) average earnings per job for the health care and social services industry along with the average earnings per job for the County we see that since the late 1970s jobs in the health care sector have provided 2 Deller, Steven C.
2011. “The Economic Contribution of Hospitals to Wisconsin.” Department of Agricultural and Applied Economics Miscellaneous Publications (November).
http://www.aae.wisc.edu/pubs/misc/docs/deller.hospital.impacts.10.26.11.pdf Total employment growth over 1969 to 2009 for La Crosse County was about 130 percent but for the health care sector employment growth for the County was just over 390 percent.
5 higher wages and salaries than the typical job in La Crosse County (Figure 5). Over the past ten years, particularly the period between 2000 and 2004, the pay scale for health care jobs has grown significantly higher than the average job. Since 2003, adjusted for inflation earnings per job has been flat and declining.
The effects of the “Great Recession” are evident in 2009, particularly for health care, but the decline in average per job earnings for the typical job is particularly troublesome. After a peak in 2003 at $37,500 the overall average has declined to $35,800 in 2009. This decline cannot be attributed to the “Great Recession” and is more a reflection of structural shifts in the economy toward more part‐time jobs that offer lower pay. A comparison of health care and social services sector average earnings per job for La Crosse County to Wisconsin and the U.S. reveals that La Crosse County tracks Wisconsin fairly closely and has been slightly above Wisconsin since 2002 (Figure 6).
But the stagnation of earnings per job growth in health care does not appear to be unique to La Crosse County. For Wisconsin and the U.S. there is a noticeable decline in earnings per health care job prior to the beginning of the “Great Recession”.
Generally, we have found that La Crosse County’s economy has been fairly strong and the health care sector appears to be a major source of job growth for the County. In addition, the average earnings for jobs created within the health care sector appear to be above the county‐wide average. Economic Contribution of the Health Care Sector In the trend analysis presented above it becomes clear that the health care sector is a source of strong employment growth and pays above average wages. Unfortunately, the health care data examined above (as well as in Appendix A) includes social service industries (e.g., child care, emergency family services, etc.).
In other words, the annual data examined above does not allow us to separate traditional health care industries (e.g., hospitals and medical clinics) and social service industries (e.g., child care, etc.). To refine our thinking we will build on the Wisconsin Hospitals Association (WHA) recently released study on the contributions of hospitals to the Wisconsin and local economies.3 Here we use a detailed input‐output model of the La Crosse County economy using data for 2009 (See Appendix B for an overview of input‐output analysis and the logic of a multiplier.) For this analysis of the contribution of the health care sector to the La Crosse County economy we explore three specific sectors: Hospitals, Offices of physicians, dentists, and other health practitioners, Nursing and residential care facilities 3 Deller (2011).
La Crosse County’s economy has been fairly strong and the health care sector appears to be a major source of job growth for the County.
*See Resources (Page 10)
6 We select these sectors primarily because of the structure of the La Crosse County economic model. One sector that we do not include is retail trade associated with health services such as pharmacists and medical supply companies (e.g., stores that specialize in selling items such as wheel chairs, walkers, etc.). Unfortunately, a large part of retail pharmacy sales now occur in general merchandise stores (e.g., Wal‐Mart and Target among others) and the health care component cannot be separated out for analysis.
In our impact analysis we use four measures of economic activity: (1) employment, (2) labor income, (3) total income, and (4) industry sales/revenue.
Employment includes both part‐ and full‐time employment and is not full‐ time equivalent. Labor income is defined as income derived from work related activities and includes wages, salary and proprietor income. Total income includes labor income plus all other sources of income including income from dividends, interest and rent as well as transfer payments such as social security and unemployment payments. Total income could be considered akin to gross county product in the spirit of gross domestic product. Industry sales/revenues are simply business sales.
Table 1: Impact of Health Care Industries on La Crosse County 2009 Employment Labor Income Total Income Industry Sales Hospitals Direct Effect 8,310 $616,954,903 $658,536,059 $1,262,158,976 Indirect Effect 2,281 $77,851,199 $153,779,911 $246,319,692 Induced Effect 3,819 $128,291,337 $224,157,875 $372,494,617 Total Effect 14,409 $823,097,438 $1,036,473,845 $1,880,973,285 Multiplier 1.734 1.334 1.574 1.490 Total County 78,554 $3,371,922,291 $5,024,037,474 $9,686,179,903 Percent of County Total Economy 18.3% 24.4% 20.6% 19.4% Impact on Neighboring WI Counties 439 $13,962,912 $24,494,194 $44,993,578 Offices of physicians, dentists, and other health practitioners Direct Effect 1,394 $88,292,484 $94,096,904 $165,414,224 Indirect Effect 313 $11,381,020 $18,824,069 $31,939,605 Induced Effect 548 $18,421,068 $32,188,463 $53,487,532 Total Effect 2,255 $118,094,572 $145,109,437 $250,841,361 Multiplier 1.618 1.338 1.542 1.516 Percent of County Total Economy 2.9% 3.5% 2.9% 2.6% Impact on Neighboring WI Counties 60 $1,887,990 $3,334,425 $5,913,822 Nursing and residential care facilities Direct Effect 1,250 $34,431,542 $37,178,352 $67,941,984 Indirect Effect 133 $4,540,952 $8,176,267 $13,904,799 Induced Effect 217 $7,270,186 $12,712,172 $21,117,121 Total Effect 1,599 $46,242,680 $58,066,791 $102,963,904 Multiplier 1.279 1.343 1.562 1.515 Percent of County Total Economy 2.0% 1.4% 1.2% 1.1% Impact on Neighboring WI Counties 25 $807,100 $1,394,756 $2,664,564 All Sectors Combined Direct Effect 10,954 $739,678,928 $789,811,315 $1,495,515,184 Indirect Effect 2,727 $93,824,622 $180,856,364 $292,316,524 Induced Effect 4,588 $154,136,484 $269,322,729 $447,549,665 Total Effect 18,269 $967,640,034 $1,239,990,408 $2,235,381,373 Multiplier 1.668 1.335 1.570 1.495 Percent of County Total Economy 23.3% 29.3% 24.7% 23.1% Impact of Neighboring WI Counties 525 $16,658,002 $29,223,375 $53,571,965
7 A summary of the analysis is provided in Table 1. Consider first the three components of the health care industry taken together. In 2009, the health care sector accounted for about 18,269 jobs, which is about 23.3 percent of all employment in the county. The computed employment multiplier is 1.668 which can be interpreted as for every additional ten jobs in the health care sector an additional 6.68 jobs will be created elsewhere in the County economy. This level of employment supports $987.6 million in labor income (wages, salaries and proprietor income), or about 29.3 percent of the County total.
The higher share of labor employment attributed to the health care industry above employment is a strong indicator of the pay scale within the health care industry. As noted above in the historical descriptive analysis, the wages/salaries paid in the health care industry tend to be higher than the County average. The labor income multiplier is 1.335 suggesting that for every $100 of additional labor income in health care will generate an additional $33.5 of labor income elsewhere in the local economy. The health care industry accounts for about $1.24 billion of total income (all forms of income), or 24.7 percent of the County total, and $2.33 billion in industrial sales or revenue, which is about 23.1 percent of the County total.
La Crosse County is not an isolated economy and as noted above is a regional retail and service hub providing services to neighboring counties. The economic linkages that are captured in multipliers can also be used to measure the linkages La Crosse County has with its neighboring counties.4 For the whole of the health care sector, there are 525 jobs, $16.6 million in labor income, $29.2 million in total income, and $53.6 million in industries sales generated in neighboring counties. This is economic activity above and beyond the impacts within La Crosse County itself. Thus the contribution of the health care sector within La Crosse County is not just a concern for La Crosse County officials and residents, but also a concern for the surrounding communities.
The economic activity that is generated and supported by the health care industry is also a source of revenues for state and local governments. Retail sales activity, for example, generates sales tax revenues, employment generates income tax revenues, and workers and businesses supported by the health care industry also pay property taxes. The over 18,000 jobs and nearly a $1 billion in income generated by the health care industry also generates about $82 million in state and local government revenues (Table 2). $17 million takes the form of sales tax, some of which (about $1.9 million) flows to the County government, $24 million in property taxes which nearly all of which flows to local governments in La Crosse County, about $18 million in income taxes which goes to state government, and $22 million in miscellaneous other taxes, fees and charges.
This analysis does not include revenues flowing to the federal government.
If we decompose the total economic impact of the health care sector into its three components as defined for this study (hospitals, clinics/offices, resident care) it becomes readily clear that for La Crosse County the industry is 4 Unfortunately, we cannot include neighboring Minnesota counties in the analysis. For this study, neighboring counties are those that are adjacent to La Crosse County in Wisconsin. Table 2: State and Local Government Revenues Generated in La Crosse Co. by Health Care Industry Impacts 2009 Hospitals Offices of physicians, dentists and other health practitioners Nursing and residential care facilities All Sectors Combined Sales Taxes $14,370,836 $1,782,650 $1,021,724 $17,185,483 Property Taxes $20,229,136 $2,517,722 $1,432,078 $24,193,199 Income Taxes $14,947,468 $2,145,456 $847,860 $17,945,573 Other $18,973,040 $2,485,270 $1,084,917 $22,553,377 Total $68,520,480 $8,932,098 $4,386,579 $81,877,632 …for every additional ten jobs in the health care sector an additional 6.68 jobs will be created elsewhere in the County.
8 dominated by hospitals. Consider just employment, hospitals account for 14,400 jobs while the offices of physicians, dentists and other health care practitioners account for about 2,250 jobs, while nursing and resident care facilities account for about 1,600 jobs once the multiplier effect is accounted for. A similar pattern applied to the three other metrics of economic activity: labor income, total income and industrial sales. Indeed, when one considered the amount of revenues flowing from the economic activity generated by these three components of the health care industry a similar pattern is observed.
Also note that the value of the multipliers varies across each of the three health care sectors. These differences in the size of the multipliers reflect how well “connected” the sector is to the local economy. Higher pay scales along with more purchases from local businesses will enlarge the multiplier. Conversely, lower pay scales and fewer purchases from local business will drive the multiplier to smaller values.
If we combine the insights we have gained from the historical analysis along with the economic impact assessment we can make several observations. The health care sector is a significant source of economic activity for La Crosse County and the surrounding area. The rate of growth of the health care sector for La Crosse County in terms of employment and income far outpaces other local industries. The wages offered in the health care industry tends to be above the typical job in the County. The Potential Economic Impact of Reductions to Medicaid and BadgerCare One of the unique aspects of the health care industry that makes it difficult to fully understand the economic contribution of the industry to the local or regional economy is the flow of funds from the federal and state government in the forms of Medicare, Medicaid, BadgerCare and a range of other programs.
The reimbursement rates paid for covered persons varies significantly across programs and services rendered. For some programs and services costs are adequately covered but for others costs are not covered and the health care provider sustains an economic loss.
Consider, for example, a farmer who is selling their products on the open market and generating significant revenues to the farm. But, if these revenues are not sufficient to cover operating costs, the farm is said to be operating at a loss. In a sense, this farmer is representing a drag on the local economy and if these losses continue indefinitely, the farm will eventually go out of business. If the operating losses are sufficiently large the multipliers, such as those provided in Table 1, can actually become negative. This creates a challenge for assessing the potential economic impact of reductions in these federal and state programs.
If there are budget cuts to a program that less than fully reimburses the cost of services rendered, will this result in a net loss or gain to the regional economy? To proceed we assume that Medicaid and BadgerCare reimbursements represent new money coming into the economy that would not be available if it were not for these programs. In order for this assumption to make sense we must presume that Medicaid and BadgerCare patients will be receiving health care services regardless of participation in the programs. This care can take many forms ranging from last minute emergency care which may be more costly or charity care.
Regardless, care must be taken when interpreting the impact results.
In 2009 the Medicaid and BadgerCare programs put $127,101,486 dollars into the health care sector in La Crosse County and in 2010 the amount was $125,661,772. There are any number of proposals being offered to offset deficits in these two programs offered by the Walker Administration and other interested parties. Complicating matters is that any final proposal must be approved by the federal government which may accept the whole proposal, parts of the proposal or reject the whole proposal. Thus, the exact level of reduction in Medicaid and If there are budget cuts to a program that less than fully reimburses the cost of services rendered, will this result in a net loss or gain to the regional economy?
9 BadgerCare funds flowing into La Crosse County is unknown at this time. The best that can be accomplished at this time is to explore what the potential magnitude of economic impacts might be. We try to provide insights into these magnitudes in three ways: (1) the impact of the whole of the payments to La Crosse County health care providers to establish a base‐line, (2) a 25 percent reduction and (3) a 10 percent reduction. To carry out the analysis we used the current (2011 to date) payment schedule to describe how these payments flow into the County health care industry. This breakout is provided in Table 3 and uses an average of the 2009 and 2010 total payments.
Table 3: Medicaid and BadgerCare payments to La Crosse Health Care Provider Type Industry Sector Share Direct MA Payment Pharmacy 22.81% $28,829,310 Hospitals 24.62% $31,116,675 Doctors Offices 17.10% $21,605,285 Individual and family services 2.51% $3,172,777 Nursing and residential care facilities 22.54% $28,480,500 Other ambulatory care services 6.58% $8,314,532 Home health care services 3.85% $4,862,551 TOTAL $126,381,630 The results of the analysis are provided in Table 4. The economic contribution of the whole of the Medicaid and BadgerCare program payments to health care providers in La Crosse County is about 1,800 jobs and $72 million in labor income, $93 million in total income and $159 million in industrial sales.
Now consider a 25 percent reduction. If health care providers respond to this cut in reimbursements by reducing staff the total economic impact could be as many as 460 jobs and $18 million in labor income.
Table 4: Potential Economic Impacts of MA Reductions Employment Labor Income Total Income Industry Sales Impact of $126,381,629 MA Payment 1,839 $72,197,936 $92,716,986 $159,414,567 Impact of 25% Reduction 460 $18,049,484 $23,179,247 $39,853,642 Impact of 10% Reduction 184 $7,219,794 $9,271,699 $15,941,457 What we do not fully understand, however, is how health care providers will respond to the reimbursement reductions. It is unlikely that medical staff will be reduced but support staff such as in food services, janitorial staff, or office support staff may be trimmed or hours reduced.
Conclusions The information and analysis presented in this report confirms the relative importance of the health care sector to the economy in La Crosse County and the surrounding area.
The rate of growth in the health care industry, in terms of employment and income, creates a high level of dependency in La Crosse County‐‐ because of its economic activity. It is feasible that cuts to Medicaid and BadgerCare funding, at whatever level, can have the greatest state‐wide impact in La Crosse County‐‐‐‐as La Crosse County has the largest multiplier effect due to the strength of the health care industry here. 5 5 Deller (2011). The cost of these expenditures shifts from the federal and state government to local (La Crosse County) health care providers and health care clients.
10 Any decisions to reduce or eliminate Medicaid and/or BadgerCare funding must consider more than the initial dollar savings of the program budget reduction to determine the economic and social impact. Reductions in these programs will naturally impact the health care sector in La Crosse County, and in turn have an impact to La Crosse County’s local employment, labor income, total income, and industry sales. In addition to the ripple effect cuts to Medicaid and BadgerCare will create, these cuts do not necessarily eliminate the expenditures, or the need for the expenditures. Instead, the cost of these expenditures shifts from the federal and state government to local (La Crosse County) health care providers and health care clients.
Individuals, families, and businesses will be required to spend more for health care and/or health insurance, resulting in less money available to reinvest in business and the community, less building projects, less job opportunities, less consumer purchases, etc.
The proposed changes for these two programs present more questions than answers: Will the cost of care for individuals/families currently receiving Medicaid or BadgerCare benefits, who lose access to health care coverage and still need care, be higher? How will individuals/families who currently receive health care coverage through their own or employer provided health insurance or private pay be impacted? If costs for health insurance or health care increases, how will their diminished consumer spending affect the local economic activity? Will health care businesses be able to continue to provide under‐funded or non‐funded services? Will the need for uncompensated and charity care increase? Will the cost for under‐funded or non‐funded services be shifted to other patients, government, taxpayers, or other patients through hyper inflated health insurance?
Will health care costs increase? Will employees lose jobs and/or benefits? Will patients lose services? How will combining the loss of these program revenues with the costs for mental health and emergency care costs impact the local tax levy and program viability? In these politically challenging times, one can be criticized for supporting publicly funded health care programs when they are overspending by $500+ million, yet supporting the elimination and/or reduction of programs results in impacts that ripple through La Crosse County’s economy, effecting more than just the financially disadvantaged.
Ultimately, we need to understand the systemic issues in our health care system that creates high costs, and find the creative answers to the question—who will bear the costs of access to and for health care in Wisconsin?
11 Resources The data for this analysis come from three sources: The historical trend analysis (Figures 1 through 6 as well as the cluster analysis in Appendix A) is from Woods and Poole, Inc, Washington DC. The core data upon which Woods and Poole builds their data is the Bureau of Economic Analysis, Regional Economic Information System (BEA‐REIS) available at: http://www.bea.gov/regional/index.htm The economic impact analysis is conducted using IMPLAN, a regional economic modeling system originally developed by the USDA Forest Service and now operated by the IMPLAN Group. Details of the modeling system and supporting data bases can be viewed at: http://implan.com/V4/Index.php La Crosse County medical transfer payments were obtained from the 2011‐2012 Blue Book (http://legis.wisconsin.gov/lrb/bb/11bb/Stats_SocialServices.pdf, pages 811‐812) and the Wisconsin Fiscal Bureau (Eric Peck, Fiscal Analyst).
12 Appendix A: Cluster Analysis In 2003 the Wisconsin Office of the Governor embraced the notion of cluster development as the foundation of economic development policies. Forward Wisconsin defines clusters as: . geographic concentrations of interconnected companies, specialized suppliers, service providers and associated institutions in a particular field. Clusters develop because they increase the productivity with which companies can compete in an increasingly more competitive global market, and they are the source of jobs, income and export growth. The philosophy behind clusters is that large and small companies in a similar industry achieve more by working together than they would individually.
Clusters give businesses an advantage by providing access to more suppliers and customized support services, skilled and experienced labor pools, and knowledge transfer through informal social exchanges. In other words, clusters enhance competitiveness.
The state initially identified 10 existing and potential clusters, including dairy and food processing. Other clusters include paper and wood products, biotechnology, plastics, medical devices, information technology and wind energy. Methods of identifying clusters vary widely, but an approach suggested by Harvard business economist Michael Porter is growing in popularity. The approach is built on the notion of location quotients: current values of the location quotient, changes in the location quotient over time, and relative size of the industry coupled with other industry characteristics.
The location quotient (LQ) is an indicator of self‐sufficiency, or relative strength, of a particular industry. The LQ is computed as: The proportion of national economic activity in sector i located in the region (state or community) measures the region's production of product i, assuming equal labor productivity. The proportion of national economic activity in the region proxies’ local consumption, assuming equal consumption per worker. The difference between local production and consumption is an estimate of production for export (i.e. production > consumption). The key assumptions to operationalize the location quotient approach are that the regional production technology is identical to national production technology (i.e.
equal labor productivity) and that local tastes and preferences are identical to national tastes and preferences (i.e. equal consumption per worker). Assuming the national economy is self‐sufficient, the comparison between the community and the national benchmark gives an indication of specialization or self‐sufficiency.
Three important location quotient values derive from the self‐sufficiency interpretation of location quotients. A location quotient of 1 means the region has the same proportion of economic activity in sector i as the nation. The region just meets local consumption requirements through local production of the specified good or service. If the location quotient is less than 1, the region is not producing enough to meet local needs. If the location quotient is greater than 1, the region has a larger proportion of its economy in sector i than does the nation. The Porter notion of clusters evaluates levels and changes of the location quotient coupled with the absolute size of the industry and other characteristics that may make the industry desirable as a source of employment opportunities.
Consider the simple mapping of the level and change of the LQ as outlined in Figure A1. There are four potential combinations.
Percent of local economic activity in sector i i s LQ ‐ ‐ Percent of national economic activity in sector i
13 First, if the industry has a LQ less than 1 and is declining, this industry is considered a “weakness and declining” industry and generally should not be considered a potential cluster. Second, if the LQ is less than 1 but increasing, the industry can be considered a “weakness and growing” industry and may be a possible industry of focus for economic development. Third, if the LQ is greater than 1 but is declining over time, it is considered “strength and declining.” Industries in this category might be considered at risk and deserving of special consideration to understand why a strong industry (i.e.
LQ>1) is weakening (i.e. ΔLQ
14 Table A1: Cluster Analysis for La Crosse County Using Employment Data LQ 2009 ∆LQ 1990‐ 2009 Share of County Employment Farm Employment 0.743 ‐0.097 1.1% Forestry, Fishing related activities and other employment 0.541 ‐0.014 0.3% Mining Employment 0.039 0.000 0.0% Utilities Employment 0.694 0.120 0.2% Construction Employment 0.758 ‐0.034 4.0% Manufacturing Employment 1.349 0.094 9.7% Wholesale Trade Employment 1.082 ‐0.458 3.8% Retail Trade Employment 1.229 0.150 12.6% Transportation and Warehousing Employment 0.873 0.107 2.8% Information Employment 0.712 ‐0.123 1.4% Finance and Insurance Employment 1.019 0.333 4.9% Real Estate and Rental and Lease Employment 0.650 0.052 2.9% Professional and Technical Services Employment 0.505 ‐0.020 3.5% Management of Companies and Enterprises Employment 1.953 0.546 2.1% Administrative and Waste Services Employment 0.557 ‐0.145 3.2% Educational Services Employment 0.779 0.007 1.8% Health Care and Social Assistance Employment 1.669 0.151 18.9% Arts, Entertainment, and Recreational Employment 0.870 ‐0.195 1.9% Accommodation and Food Services Employment 1.190 ‐0.122 7.6% Other services, except Public Administrative Employment 0.892 ‐0.133 5.2% Federal Civilian Government Employment 0.343 ‐0.022 0.6% Federal Military Employment 0.338 ‐0.050 0.4% State and Local Government Employment 0.964 ‐0.062 11.2% Data represented in Figure A2
15 Appendix B: The Logic of a Multiplier The analysis, as presented, considers the total economic contribution of the health care sector to La Crosse County, Wisconsin. Specifically, how do the approximately 11,000 health care sector jobs and the economic activity associated with those jobs (i.e., industry sales and labor income) impact the remainder of the La Crosse County economy? For example, hospital workers spend their wages and salaries in the local economy: they spend money in local grocery stores, local restaurants and go out to the movies. In addition hospitals pay utility bills, buy office equipment and supplies, and pay taxes among other expenses.
This spending by hospital employees and the hospital itself in the local economy generates what is referred to as a multiplier effect. To answer this question we use a family of regional economic models referred to input‐output analysis. An input‐ output model can be described as a “spreadsheet of the economy” capturing the demand and supply of the different actors (industries and institutions such as households, government or imports/exports) that make up that economy. Demanders or consumers are across the columns of the “spreadsheet” and suppliers or sellers are down the rows. Any individual cell of the “spreadsheet” captures the flow of money from demanders (consumers or buyers) to suppliers (sellers).
Thus reading down the column of any particular demander (e.g., industry) outlines how the demander spends money. For an industry, such as hospitals, reading down the column reveals the “production function” of the industry. For a given level of production how much labor or electricity or accounting services do hospitals need to purchase? At the same time reading across the row of a supplier tells us who that industry is selling to. Grain farmers, for example, could be selling to dairy farmers, food processors, directly to households or exporting their product out of the region.
Given that the economy is in “equilibrium” or more specifically supply must equal demand for all industries we can use this “spreadsheet” representation of the economy to capture how changes in one part of the economy influence or impact other parts of the economy. For example, if a medical clinic expands operations it must purchase more inputs (e.g., labor, utilities, accounting services) and the industry that supplies those inputs must increase their own production to meet that new demand. This “ripple” effect is commonly referred to as the multiplier effect. Not only can we measure the total impact or contribution of any given industry on the whole of the economy but also what industries are impacted and to what extent.
The size of an economic multiplier hinges on two concepts. The first is the level of linkages an industry has with other businesses within the local economy. The second is the notion of “leakages” and the ability of the local economy to retain dollars. How many inputs that a particular business purchases can and are purchased in the local economy. For example, can a mining company buy the specialized equipment that it requires from local businesses or does the company buy that equipment from businesses from outside the local area? Because so much of the larger pieces of equipment the mining companies will require are so specialized, the likelihood of buying this equipment in the local economy is small.
This represents a “leakage” from the local economy. Consider a simple visual representation of the logic of a multiplier (Figure B1). Consider a newly employed worker at a medical clinic is paid $1. This worker spends this new income in the local economy. Suppose, for example, this worker spends that $1 at a local grocery store. The question is how much of that dollar spent at the grocery store stays in the local economy. In this example, 60¢ leaks out of the economy and goes to pay for the vegetables from California, the canned goods from Texas, and the boxed goods from Illinois. In other words, the grocer must pay for the stock in the store.
Here the grocer keeps 40¢ and uses that 40¢ to pay, perhaps the utility bill. That represents 40¢ going to the local utility company. Now suppose the local utility company uses Montana coal to create the electricity the grocer is buying. In this example, 24¢ of that 40¢ immediately leaves (or leaks out) the local economy and goes to Montana. Suppose the utility company uses the remaining 16¢ to pay its employees. Now suppose that utility worker takes that 16¢ and takes the family to the movies. Part of that 16¢ immediately leaves the local economy and goes to Hollywood to pay for the movie itself.
This respending continues till all of the money leaks out of the economy. In this example, the economic multiplier is 1.66: for every dollar of new activity creates $1.66 in economic activity, the original dollar plus 66¢ through the multiplier effect.
16 Initial $1.00 of exports 40¢ respent locally 60¢ leakage 16¢ respent locally 24¢ leakage 6¢ respent locally 10¢ leakage 3¢ respent 3¢ leakage (a) (b) (c) (d) (e) (f) 2¢ leakage 1¢ respent locally Initial impact: $ 1.00 .40 .16 .06 .03 .01 - - Full impact: $ 1.66 Figure B1: Multiplier Logic Generally, the size of the multiplier will reflect the size of the local economy. Larger more urban economies tend to have larger multipliers than smaller more rural economies. The key here is the ability of larger economies to capture and retain those dollars being spent. For smaller economies, like much of western Wisconsin, the ability to retain those dollars is weaker, money will leak out of the local economy faster, and the multiplier will be smaller.