Rising Inequality in an Era of Austerity: The Case of the USA

Presented by Mark PartridgeSwank Professor in Rural Urban PolicyThe Ohio State UniversityOctober 13, 2013 AUBER Conference Richmond, VA Modeling Economic Development Impacts: We can do better?

1Thanks to Dan Rickman for his comments and suggestions.1Introduction/Background The general credibility of impact studies have long been questioned by academics and members of the public. One problem is that they tend to paid for by industry interests.Another possible concern is that they are typically based on purchased software packages that use input-output/SAM methodologies or eclectic packages that add some econometric assumptions about migration and other assumptions about agglomeration economies. See Partridge and Rickman (1998; 2010).One problem is that the methodologies are not best practice in identifying counterfactuals.2Partridge, Mark D. and Dan S. Rickman. (2010) CGE Modeling for Regional Economic Development Analysis. Regional Studies, 44: 1311-1328. doi: 10.1080/00343400701654236.Partridge, Mark D. and Dan S. Rickman. "Regional Computable General Equilibrium Modeling: A Survey and Critical Appraisal." International Regional Science Review 21 (#3, 1998): 205-250.

2Introduction/Background3AUBER centers try to play more straight with economic impact predictions because of their desire to maintain academic credibility.Yet, Auber centers typically use the same vendor software(s) to estimate impacts. [time constraints]Of course, AUBER affiliates feel pressure to please clients.Can we do better in providing economic impacts that are more credible?I argue yes. Computable General Equilibrium models (CGE), better econometric models, and more attention to external validity are key steps in this process.

Introduction/Background4OutlineDescribe the need to employ external validity.Review typical impact models and appraise their strengths and weaknesses. Review an example from energy of how impact assessments can get out of control. Describe CGE models and appraise their strengths and weaknesses.Describe alternative econometric approaches.

External Validity5External Validity: is the extent to which the results of a study can be generalized to other situations and to other people. Inferences about cause-effect relationships based on a specific scientific study are said to possess external validity if they may be generalized from the unique and idiosyncratic settings, procedures and participants to other populations and conditions. Wikipedia, http://en.wikipedia.org/wiki/External_validity, downloaded Sept. 26, 2013.I will argue that similar economic shocks that occurred in similar places have more external validity then results from most economic models.The economic impacts of a plant opening in a similar location will be a better predictor of what will happen in your location after a plant opening than the output of a canned impact software package.It is like using Madden 13 to predict the Super Bowl winner when we already know the outcomethe Ravens Won.At the very least, compare (say) IMPLAN results to actual results elsewhere.

Bloomberg News Article6

http://www.bloomberg.com/news/2013-03-14/california-fracking-may-boost-state-economy-14-usc-says.html6Example7Lets use my prior discussion of external validity to assess whether such claims make any sense?What is a reasonable case to apply external validity for a large oil boom?

Picking WinnersThis Time is Different8What about fossil fuels? Both Presidential candidates trumpeted recent innovations as cornerstones to their job creation strategy.Ancillary is the Keystone Pipeline and job creation. Massive media campaigns in the energy industry trumpeting job creation.

Bakken Oil Production

Source: North Dakota Industrial Commission, Department of Mineral Resources, Oil and Gas Division Montana Department of Natural Resources and Conservation, Oil and Gas Division Over 700,000bbl by Dec 2012, probably nearing 800,000 todayBakken Oil Counties defined by direct employment

Montrail, McKenzie, Richland, and Williams total population in 2006 was 41,9426826, 5727, 9267, 20122Bakken Counties: all counties in the Bakken area with at least 10% increase in oil and gas employment and at least 20 additional oil and gas workers except Burleigh County where there is no drilling.

10Bakken Media Reportsseekingalpha.com

Http://seekingalpha.com/article/1128541-the-bakken-oil-and-employment-boom-just-what-the-u-s-needsWalmart cant keep shelves stocked.11Unemployment RateSource: U.S. BLS

12Bakken EmploymentSince 2002 Bakken employment has increased from 118,500 to 167,800 in 2012 (an increase of over 49,000)Source: U.S. BLS, QCEWhttp://www.bls.gov/cew/

Bakken Counties: all counties in the Bakken area with at least 10% increase in oil and gas employment and at least 20 additional oil and gas workershttp://www.bls.gov/lau/ ND Bakken: Billings, Bottineau, Burke, Bowman, Dunn, Mercer, Mountrail, Renville, Stark, Williams, Ward, Mckenzie, SlopeMT Bakken: Richland, Roosevelt

13External Validity and California14If North Dakotas Bakken region only created 49,000 jobs with a massive oil boom, it is hard to fathom how an oil boom in California, with dense population and environmental regulations that would slow development, could create 2.8 million jobs over the 2013-2020 period.Use of external validity can avoid embarrassing forecasts.Traditional Impact Studies: Certainly not best practice.15Discussion follows Partridge and Rickman (1998;2010).Traditional impact studies are typically of two types:Most popular are input-output/SAM orientede.g. IMPLAN.Eclectic models that incorporate input-output and econometric modelinge.g., REMI.Why?1. Well known.2. Relatively easy to use and IMPLAN is especially low-cost.3. Especially with IMPLAN, the modeling can be done very fast.

Traditional Impact Modeling. 16The problems with traditional impact analysis are well known. (I will emphasize the I-O/SAM concerns).The founding father of IO, Wassily Leontief, was interested in Central Planning and the most widely used IO models lack prices.Impact studies of direct and indirect effects are typically over-estimates of new job creation (jobs supported) and academic regional economists have not viewed them as anywhere near best practice for decades. Edmiston (2004) is a good ex post evaluation of economics impacts. Very small effects are consistent with the natural/man-made disaster literature (Davis and Weinstein, 2002; Xiao, 2011). Long-run growth path.

Edmiston, Kelly D. 2004. The Net Effects of Large Plant Locations and Expansions of County Employment. Journal of Regional Science 44: 289-319.Davis, Donald R. and David E. Weinstein. 2002. Bones, Bombs, and Break Points:The Geography of Economic Activity. American Economic Review 92: 1269-1289.Xiao, Y. (2011), LOCAL ECONOMIC IMPACTS OF NATURAL DISASTERS. Journal of Regional Science, 51:804820. doi:10.1111/j.1467-9787.2011.00717.x

16Traditional Impact Modeling17A typical impact study should tell how many jobs are supported by an industry, not how many jobs it created. At the very least, this needs to be much better explained.Also the timing of jobs needs to be more transparente.g., the temporary nature of construction vs. other jobs. Confidence intervals should be reported.The general problem is that the IO models are not linked to spatial equilibrium modeling and do not reflect the displacement effects from a positive shock and they do not account for changes in entrepreneurial behavior. There are approaches that account for these concerns in the natural experiment literature and matching. More on this below.

Traditional Impact Modeling18One suggestion to provide more honesty to traditional impact modeling is that confidence intervals be reported. Vendors should incorporate simple Monte Carlo based bootstrap procedures to estimate the standard errors of the estimates. This is something that has been done with CGE models (Partridge and Rickman, 1998, 2010). It would be doable for vendors to provide.Another suggestion is to use actual data from similar shocks to assess whether the software is producing reasonable results.External validity.

Traditional Impact Modeling19Example of using actual data and external validity for traditional impact results.Ohio Shale Energy Boom.Kleinhenz & Associates (2011) funded by the industry predicted over 200,000 jobs in Ohio by 2015. Used REMI.Ohio Shale Coalition (2012) predicted 66,000 jobs by 2014. Used IMPLANWeinstein and Partridge (WP) (2011) predicted 20,000 by 2015.WP noted that Pennsylvania had a boom that proceeded Ohios and given the similarities of the two states, used the direct employment effects in PA for the first 4-5 years of their boomwhich they generously estimated at 10,000 (counted some indirect effects or double counted). Then using a multiplier of 2, WP estimated 20,000 jobs for Ohio.Reporting actual data, through Qtr 1 2013, employment growth in the strong shale regions is imperceptibly different from the rest of the state (College of Urban Affairs, Cleveland State University, 2013). This suggests WP appear to be correct.

Kleinhenz and Associates. Ohios Natural Gas and Crude Oil Exploration and Production Industry and the Emerging Utica Gas Formation. (Sept., 2011)Ohio Shale Coalition. (March 2012) AN ANALYSIS OF THE ECONOMIC POTENTIAL FOR SHALE FORMATIONS IN OHIO. Available at: urban.csuohio.edu/.../center/.../Ec_Impact_Ohio_Utica_Shale_2012.pdf.College of Urban Affairs, Cleveland State University, 2013. Ohio Utica Shale Region Monitor. Available at: urban.csuohio.edu/.../hill/OhioUticaShaleRegionMonitor_Mar2013.pdfWeinstein, A. & Partridge, M. (2011 December). The economic value of shale natural gas in Ohio. Swank Program in Rural-Urban Policy Summary and Report. Retrieved from http://aede.osu.edu/sites/drupal-aede.web/files/ Economic%20Value%20of%20Shale%20Dec%202011.pdf 19CGE Modeling20Partridge and Rickman (2010) are optimistic that regional CGE models can be constructed with realistic migration, capital location, and commuting effects. P&R offer suggestions to further improve their accuracy in which they too often mimic international models. CGE models flexible enough to analyze many impacts such as land use, tax policy, income distribution, and employment shocks. My first 2 publications constructed an early regional CGE model to assess tax policy (Morgan et al., 1989; Mutti et al., 1989).CGE models have the key advantage of using a structural framework make them . As someone who has built these models and a reviewer-editor for dozens of CGE papers, their results are quite robust to even non marginal changes in key parameters.Why, offsetting price changes allow the model to remain stable. Morgan, William, John Mutti and Mark D. Partridge. "A Regional General Equilibrium Model of the United States: Tax Effects on Factor Movements and Regional Production." Review of Economics and Statistics 71 (November 1989): 626-635.Mutti, John, William Morgan and Mark D. Partridge. "The Incidence of Regional Taxes in a General Equilibrium Framework," Journal of Public Economics 39 (June 1989): 83-108.

20CGE Models21Case closed, lets switch to CGE models. Right?There are some constraints. The biggest is that there is still no canned programs and they are not easy to build. Yet there are wonderful examples of regional CGE models that could be employed:1. AMOS at the University of Strathclyde. Harrigan et al., 1991.2. Colorado State University Modele.g., Burnett et al., 2012; Cutler and Davies, 2010; Schwarm and Cutler, 2003.3. Federal-F for Australia-- Giesecke and Madden, 2003a, b.4. The late David Holland at Washington State had a model of the Washington state economyCassey et al., 2011.The take away is that I urge you to look into CGE modeling for your work.

Burnett, Perry, Harvey Cutler and Stephen Davies. 2012. Understanding the Unique Impacts of Economic Growth Variables. Journal of Regional Science, 52(3): 451-468.Cutler, Harvey and Stephen Davies. 2010. The Economic Consequences of Productivity Changes: A Computable General Equilibrium (CGE) Analysis. Regional Studies 44 (10): 1415-1426.Harrigan, F., McGregor P., Perman R., Swales K. and Yin Y., (1991), AMOS: A Macro-Micro Model of Scotland, Economic Modelling, vol. 8, 424-479.SCHWARM W. and CUTLER H. (2003) Building small city and town SAMS and CGE models, Review of Urban and Regional DevelopmentStudies 15, 132147.GIESECKE J. and MADDEN J. R. (2003a) A large-scale dynamic multi-regional CGE model with an illustrative application, Reviewof Urban and Regional Development Studies 15, 225.GIESECKE J. and MADDEN J. R. (2003b) Regional labour market adjustment to competition policy reforms: a dynamic CGEframework for assessment, Australian Journal of Labour Economics 6, 409433.Cassey, Andrew J., David W. Holland and Abdul Razack. 2011. Comparing the Economic Impact of an Export Shock in Two Modeling Frameworks Applied Economic Perspectives and Policy, 33 (4): 62363821Econometric Solutions22Marchand, J. 2012. Local Labor Market Impacts of Energy Boom-Bust-Boom inWestern Canada. Journal of Urban Economics 71: 165-174.

22Econometric solutions23INDMIX could be constructed for individual sectors to get multipliers by sector. Marchand (2012) describes sectoral multipliers.The outcome is that you could create multipliers based on real world behavior (with confidence intervals) rather than being the outcome of model that doesnt produce standard errors.Econometric Solutions24Simple matching of places receiving the treatment and those who did not can be employed. It could employ regression approaches to control for observables or even simple t-statistics on differences.In this case, the counterfactual is similar places that had similar economic characteristics and trends prior to the treatment. This can be done with statistical software and identifying treatment as (for example) places that had a big change in employment in a certain sector. A really simple example is what we did to assess the early impacts of the Pennsylvania shale boom. We found modest effects on employment and large impacts on income.25

PA Counties considered in our simple difference in difference counterfactualSource: U.S. Bureau of Economic Analysis, REIS Data, Downloaded Oct. 7, 2011. www.bea.gov

27The sum of the three mining counties and the sum of the three non-mining counties.In Southern PA, the three mining counties are: Washington, Greene, and Fayette. They are chosen for heavy mining activity.In Southern PA, the three non-mining counties are: Perry, Franklin, and Cumberland. They are chosen due to have similar urban-ness and be geographically close but not TOO close to have spillovers.

27Source: U.S. Bureau of Economic Analysis, REIS Data, Downloaded Oct. 7, 2011. www.bea.go

28The sum of the three mining counties and the sum of the three non-mining counties.In Northern PA, the three mining counties are: Susquehanna, Tioga, Bradford. They are chosen for heavy mining activity.In Northern PA, the three non-mining counties are: Carbon, Union, and Columbia. They are chosen due to have similar urban-ness and be geographically close but not TOO close to have spillovers.28Source: U.S. Bureau of Economic Analysis, REIS Data, Downloaded Oct. 7, 2011. www.bea.gov

29The sum of the three mining counties and the sum of the three non-mining counties.In Southern PA, the three mining counties are: Washington, Greene, and Fayette. They are chosen for heavy mining activity.In Southern PA, the three non-mining counties are: Perry, Franklin, and Cumberland. They are chosen due to have similar urban-ness and be geographically close but not TOO close to have spillovers.

29Source: U.S. Bureau of Economic Analysis, REIS Data, Downloaded Oct. 7, 2011. www.bea.gov

30The sum of the three mining counties and the sum of the three non-mining counties.In Northern PA, the three mining counties are: Susquehanna, Tioga, Bradford. They are chosen for heavy mining activity.In Northern PA, the three non-mining counties are: Carbon, Union, and Columbia. They are chosen due to have similar urban-ness and be geographically close but not TOO close to have spillovers.

30Econometric Approaches31There are more complicated matching approaches but finding simple treatment cases and comparing to similar non-treatment cases provides real-world predictions of what to expect.Conclusions/Summary32Economic Impact modeling often uses non-structural models to estimate impacts. These models are often criticized for producing overestimates of the economic impacts.I described some ways to improve the estimates and enhance the credibility of their predictions.1. Use external validity in confirming forecasts.2. Provide confidence intervals on the estimates of models using Monte Carlo bootstrapping. 3. Provide a better interpretation of the timing of multipliers and the meaning of jobs supported versus net job creation.Conclusions/summary334. Use structural CGE models which have a clear counterfactual.5. Use econometrics approaches such as estimation of multipliers for total employment growth or employment growth by sector and matching approaches. Matching in particular is linked to a clear counterfactual.However, it is clear that we can improve from the status quo with more attention on actual data from actual economic impacts can produce more credible estimates.