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Avoiding Taxes at Any Cost: The Economics of Tax-Deferred Real Estate Exchanges

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Abstract

This study examines the role tax-deferred exchanges play in the determination of reservation and transaction prices in U.S. commercial real estate markets. Taxpayers face significant time constraints when seeking to complete a delayed tax-deferred exchange. In a perfectly competitive market, a weakened bargaining position would not affect the transaction price. However, in illiquid, highly segmented commercial real estate markets, the exchanger may be required to pay a premium for the acquired property relative to its fair market value. Using a unique and rich dataset of commercial property transactions, we find that tax-motivated exchange buyers pay significantly more, on average, than non-exchange investors for their apartment and office properties, all else equal. Moreover, these average price premiums generally exceed the tax deferral benefits investors obtain by the use of a tax-deferred exchange. This result is robust to a number of alternative specifications. Thus, for many investors the pursuit of tax avoidance comes at a steep price.

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Notes

  1. See, for example, Glower et al. (1998), Turnbull and Sirmans (1993), Harding et al. (2003a, b).

  2. Exceptions include papers by Colwell and Munneke (2006), Holmes and Slade (2001), Shilling et al. (1990), Forgey et al. (1994), Hardin and Wolverton (1996), Lambson et al. (2004), and Hardin and Wolverton (1999).

  3. A portion of the realized gain will be recognized in the tax year in which the exchange occurs to the extent that the value of the relinquished property exceeds the value of the replacement property.

  4. With the development of IRS regulations concerning Section 1031, tax-deferred exchanges are also used to trade lines of business, such as such as television and radio stations, newspapers, distributorships, and franchises, including, among others, sports teams, beer distributorships, and professional service practices (McBurney 2004). Because a line of business includes multiple classes of assets—real, personal and intangible property—an exchange for each class needs to be completed (McBurney and Boshkov 2003; McBurney 2004).

  5. Internal Revenue Code, Title 26, Section 1001(c) (2006).

  6. The adjusted tax basis is equal to the original cost basis (including the value of the land), plus the cost of any capital improvements undertaken since acquisition of the property, minus cumulative depreciation.

  7. Like kind means “similar in nature or character.” In fact, virtually any real estate is like-kind to any other real estate. However, real property is not like-kind to personal property. Therefore, for example, a warehouse cannot be exchanged for jewelry. In addition, foreign property cannot be exchanged for U.S. property. See IRC 2006, Title 26, Section 1031.

  8. Tax deferral turns into permanent tax savings upon the death of the taxpayer because the basis of the property is “stepped-up” to its current fair market value. Thus, the taxpayer’s heirs can dispose of the property in a fully taxable sale and not have to pay taxes on gains deferred through the prior use of one or more Section 1031 exchanges.

  9. The qualified intermediary is an independent agent who facilitates the exchange. The qualified intermediary takes an assignment of rights in the sale of the relinquished property and the purchase contract for the replacement property. In short, the QI buys and then resells the two properties for a fee.

  10. More specifically, the taxpayer can (1) identify up to three properties of any value or (2) identify more than three properties so long as their combined values do not exceed 200 percent of the value of the relinquished property.

  11. Starker vs. United States, 602 F. 2d 1341 (9th cir., 1979)

  12. Since 2003, a percentage ownership interest as a tenant-in-common (TIC) is qualified property for the purposes of a Section 1031 exchange. The taxpayer, however, must be careful that the TIC has been structured to avoid its recharacterization by the IRS as a partnership for federal income tax purposes.

  13. Vacation homes will only qualify if they have been rented out the majority of the year.

  14. An additional disadvantage is that Section 1031 exchanges do not allow for the recognition of a loss for tax purposes. Thus, taxpayers will avoid using exchanges if they have not realized positive capital gain, which introduces a potential selection bias as to who participates in the exchange market.

  15. Congressional legislation has repeatedly altered the period of time over which rental real estate may be depreciated. As of 2007, residential real property (e.g., apartments) may be depreciated over no less than 27 and 1/2 years. The cost recovery period for nonresidential real property (e.g., shopping centers, industrial warehouses, and office buildings) is 39 years.

  16. From 1997 to May 6, 2003, the maximum capital gain tax rate was 20%.

  17. See http://www.costar.com/products/comps.

  18. Other exchange types include direct (simultaneous) exchanges, reverse exchanges, and exchanges involving tenancy-in-common properties.

  19. The remaining seven property types are office/residential, office with street level retail, office park, office condominium, office planned unit development, and veterinary hospital/clinic.

  20. Discussions of the impact of search costs on buyer behavior can be found in Haurin (1988), Miceli (1989), Forgey et al. (1996) and Arnold (1999).

  21. In a “reverse” exchange, the replacement property is purchased before the sale of the relinquished property. Thus, the seller of the relinquished property is negotiating at a competitive disadvantage relative to other sellers. Our dataset does not include a large enough sample of reverse exchanges to examine empirically how the pricing of such exchanges varies from delayed exchanges and fully taxable sales. We therefore do not discuss reverse exchanges here.

  22. The choice of functional form is extremely important in hedonic regression and little theory exists to guide the choice. Weirick and Ingram (1990) argue that the linear form has serious deficiencies from a market theory standpoint because the marginal contribution to value of variables such as square footage and lot size is not likely to be constant. The semi-log and log-linear models, in contrast, assume a nonlinear relation between sale price and the explanatory values.

  23. One notable exception to this general trend in price appreciation after 2002 is Dallas/Forth Worth, which is the only office market in which no price appreciation is observed.

  24. About 56% of the apartment properties have a sales price less than one million; for the office sample this percentage is 42%.

  25. This result is robust to our treatment of location.

References

  • Arnold, M. A. (1999). Search, bargaining and optimal asking prices. Real Estate Economics, 27(3), 453–481.

    Article  Google Scholar 

  • Case, B., Clapp, J., Dubin, R., & Rodriguez, M. (2004). Modeling spatial and temporal house price patterns: A comparison of four models. Journal of Real Estate Finance and Economics, 29(2), 167–191.

    Article  Google Scholar 

  • Clapp, J. (2003). A semiparametric method for valuing residential locations: Application to automated valuation. Journal of Real Estate Finance and Economics, 27(3), 303–320.

    Article  Google Scholar 

  • Colwell, P. F., & Munneke, H. J. (2006). Bargaining strength and property class in office markets. Journal of Real Estate Finance and Economics, 29, 197–213.

    Article  Google Scholar 

  • Davidson, R., & MacKinnon, J. G. (1993). Estimation and inference in econometrics. New York: Oxford University Press.

    Google Scholar 

  • Epple, D. (1987). Hedonic prices and implicit markets: Estimating demand and supply functions for differentiated products. Journal of Political Economy, 95(1), 59–80.

    Article  Google Scholar 

  • Fickes, M. (2003). 1031 Exchanges do more than save taxes. National Real Estate Investor, January, 59–62.

  • Fik, T., Ling, D., & Mulligan, G. F. (2003). Modeling spatial variation in housing prices: A variable interaction approach. Real Estate Economics, 31(4), 623–646.

    Article  Google Scholar 

  • Forgey, F. A., Rutherford, R. C., & Springer, T. M. (1996). Search and liquidity in single family housing. Real Estate Economics, 24(3), 273–292.

    Article  Google Scholar 

  • Forgey, F. A., Rutherford, R. C., & VanBuskirk, M. L. (1994). Effects of foreclosure status on residential selling price. Journal of Real Estate Research, 9(3), 313–318.

    Google Scholar 

  • Glower, M., Haurin, D., & Hendershott, P. H. (1998). Selling time and selling price: The influence of seller motivation. Real Estate Economics, 26(4), 719–740.

    Article  Google Scholar 

  • Griliches, Z. (Ed.) (1971). Price indexes and quality change. Cambridge, MA: Harvard University Press.

  • Halvorsen, R., & Palmquist, R. (1980). The interpretation of dummy variables in semilogarithmic equations. American Economics Review, 70(3), 474–475.

    Google Scholar 

  • Hardin, W. G., III, & Wolverton, M. L. (1996). The relationship between foreclosure status and apartment price. Journal of Real Estate Research, 12(1), 101–109.

    Google Scholar 

  • Hardin, W. G., III, & Wolverton, M. L. (1999). Equity REIT property acquisitions: Do apartments REITs pay a premium? Journal of Real Estate Research, 17, 113–126.

    Google Scholar 

  • Harding, J. P., Knight, J. R., & Sirmans, C. F. (2003a). Estimating bargaining effects in hedonic models: Evidence from the housing market. Real Estate Economics, 31(4), 601–622.

    Article  Google Scholar 

  • Harding, J. P., Rosenthal, S. S., & Sirmans, C. F. (2003b). Estimating bargaining power in the market for existing homes. The Review of Economics and Statistics, 85(1), 178–188.

    Article  Google Scholar 

  • Haurin, D. (1988). The duration of marketing time of residential housing. Journal of the American Real Estate and Urban Economics Association, 16(4), 396–410.

    Article  Google Scholar 

  • Holmes, A., & Slade, B. A. (2001). Do tax-deferred exchanges impact purchase price? Evidence from the phoenix apartment market. Real Estate Economics, 29(4), 567–588.

    Article  Google Scholar 

  • Internal Revenue Code, Title 26, Section 1001(c) (2006). Available via http://www.law.cornell.edu/uscode/html/uscode26/usc_sec_26_00001001----000-.html. Cited 26 June.

  • Internal Revenue Code, Title 26, Section 1031 (2006) Available via http://www.law.cornell.edu/uscode/html/uscode26/usc_sec_26_00001031----000-.html. Cited 26 June 2006.

  • Lambson, V., McQueen, G., & Slade, B. (2004). Do out-of-state buyers pay more for real estate? An examination of anchoring-induced bias and search costs. Real Estate Economics, 32(1), 85–126.

    Article  Google Scholar 

  • McBurney, C. M. (2004). Section 1031 exchanges: A legitimate tax shelter for business. Thompson FindLaw, May.

  • McBurney, C. M., & Boshkov, S. (2003). Is an attribute of an intangible in a 1031 exchange a separate asset or inherent in an existing asset. Journal of Taxation, 98(1), 46–53.

    Google Scholar 

  • McLinden, S. (2004). 1031 Exchanges test the waters. National Real Estate Investor, June, 45–47.

  • Miceli, T. J. (1989). The optimal duration of real estate listing contracts. Journal of the American Real Estate and Urban Economics Association, 17(3), 267–277.

    Article  Google Scholar 

  • Rosen, S. (1974). Hedonic prices and implicit markets: Product differentiation in pure competition. Journal of Political Economy, 82(1), 34–55.

    Article  Google Scholar 

  • Shilling, J., Benjamin, J., & Sirmans, C. F. (1990). Estimating net realizable value for distressed real estate. Journal of Real Estate Research, 5(1), 129–140.

    Google Scholar 

  • Starker vs. United States, 602 F. 2d 1341 (9th cir., 1979).

  • Turnbull, G. K., & Sirmans, C. F. (1993). Information, search and house prices. Regional Science and Urban Economics, 23(4), 545–557.

    Article  Google Scholar 

  • Wayner, S. A. (2005a). 1031 exchanges defer tax bills and boost broker commissions. Real Estate Finance, February, 31–32.

  • Wayner, S. A. (2005b). Section 1031 exchanges: Underused tax-planning tool. CPA Journal, June, 16–17.

  • Weirick, W., & Ingram, F. (1990). Functional form choice in applied real estate analysis. Appraisal Journal, January, 57–73.

  • Weller, L. S., & Halfacre, D. A. (2004). Section 1031 market continues to grow. Deloitte Tax LLP.

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Acknowledgements

We thank CoStar Group, Inc. for providing the data used in this study. We also thank Lynn Fisher, Wayne Archer, Andy Naranjo, seminar participants at Syracuse University, and participants in the 2006 Maastricht-Cambridge-MIT International Real Estate Finance & Economics Symposium for the helpful comments and suggestions.

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Authors and Affiliations

  1. Department of Finance, Insurance and Real Estate, Warrington College of Business, University of Florida, Gainesville, FL, 32611, USA

    David C. Ling

  2. Department of Finance, Whitman School of Management, Syracuse University, Syracuse, NY, 13244, USA

    Milena Petrova

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  1. David C. Ling
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  2. Milena Petrova
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Correspondence to David C. Ling.

Appendix

Appendix

Table 8 Incremental NPV of non-residential exchange as a percent of replacement property value
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Table 9 Regression statistics for OLS model with structural characteristics and submarket dummies by apartment markets
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Table 10 Regression statistics for OLS model with structural characteristics and submarket dummies by apartment markets
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Table 11 Regression statistics for OLS model with structural characteristics and submarket dummies by office markets
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Table 12 Regression statistics for OLS model with structural characteristics and submarket dummies by office markets
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Ling, D.C., Petrova, M. Avoiding Taxes at Any Cost: The Economics of Tax-Deferred Real Estate Exchanges. J Real Estate Finan Econ 36, 367–404 (2008). https://doi.org/10.1007/s11146-007-9099-6

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