Tierra Grande - April 2016

APRIL 2016 ™

JOURNAL OF THE REAL ESTATE CENTER AT TEXAS A&M UNIVERSITY

COLLEGE STATION, TEXAS 77843-2115

In This Issue Texas Housing Supply Commercial Construction Water Planning for the Future Real Estate Legislation Midland/Odessa Housing Markets Staying in Good with the IRS

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APRIL 2016 ™

JOURNAL OF THE REAL ESTATE CENTER AT TEXAS A&M UNIVERSITY

FINDING A COMPLETE OVERVIEW OF THE TEXAS ECONOMY IS AS EASY AS

Our monthly economic update of everything from housing to jobs, from energy to trade. www.recenter.tamu.edu/research/the-texas-economy iii

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APRIL 2016

VOLUME 23, NUMBER 2 ™

TIERRA GRANDE JOURNAL OF THE REAL ESTATE CENTER AT TEXAS A&M UNIVERSITY

6

Nonresidential Construction and the Texas Business Cycle

Director, GARY W. MALER

New Center research shows that the commercial (nonresidential) real estate cycle does not follow the ups and downs of the Texas economy.

BY LUIS B. TORRES AND HAROLD D. HUNT

Chief Economist, JAMES P. GAINES Senior Editor, DAVID S. JONES Managing Editor, NANCY MCQUISTION Associate Editor, BRYAN POPE Assistant Editor, KAMMY BAUMANN Art Director, ROBERT P. BEALS II Graphic Specialist/Photographer, JP BEATO III Circulation Manager, MARK BAUMANN Lithography, RR DONNELLEY, HOUSTON ADVISORY COMMITTEE: Russell Cain, Port Lavaca, chairman; Doug Jennings, Fort Worth, vice chairman; Mario A. Arriaga, Conroe; Jacquelyn K. Hawkins, Austin; Walter F. “Ted” Nelson, Houston; Doug Roberts, Austin; Kimberly Shambley, Dallas; Ronald C. Wakefield, San Antonio; C. Clark Welder, San Antonio; and Bill Jones, senting the Texas Real Temple, ex-officio repre­ Estate Commission.

TIERRA GRANDE ™ (ISSN 1070-0234) is published quarterly by the Real Estate Center at Texas A&M University, College Station, Texas 77843-2115.

Telephone: 979-845-2031.

SUBSCRIPTIONS free to Texas real estate licen­ sees. Others can download articles free at www. recenter.tamu.edu.

VIEWS EXPRESSED are those of the authors and do not imply endorsement by the Real Estate Center, Mays Business School or Texas A&M University. The Texas A&M University System serves people of all ages, regardless of socioeconomic level, race, color, sex, religion, disability or national origin.

PHOTOGRAPHY/ILLUSTRATIONS: JP Beato III, pp. 1, 6–7, 13, 22; Robert Beals II, pp. 2–3, 5, 17, 18, 24; Real Estate Center files, pp. 11, 14–15, 16, 19. © 2016, Real Estate Center. All rights reserved.

2 On the Rise Again

Abundant Land Keeps Texas Flexible Land, lots of land under starry skies above.

Texas has it, and acquiring it is easier than in other states. That’s the cornerstone of Texas’ flexible housing supply.

BY ALI ANARI

14 Gauging Groundwater

Texas is ahead of the game in planning to meet increasing water demand as its population grows. Here’s what’s been done so far.

BY CHARLES E. GILLILAND

ON THE COVER King Oaks in Iola, Texas

PHOTOGRAPHER JP Beato III

APRIL 2016

20 Glad You Asked Questions from Readers

22

Oil’s Impact on Midland and Odessa Housing As oil prices and employment slipped, data reveal that Midland’s and Odessa’s housing markets showed no major negative impacts through 2015.

BY HAROLD D. HUNT

28 ‘Good Facts,’ Less Tax?

Want to stay in the IRS’ good graces? “Good facts” are similar to good grades in school. How do you earn them? Plan your tax strategy carefully and document, document, document.

BY JERROLD J. STERN

Legislative changes to real estate laws confused some of our readers (and us, too). Here is a bit of clarification our attorney was able to winnow out.

BY JUDON FAMBROUGH

1

Residential

On the Rise Again Abundant Land Keeps Texas Flexible

By Ali Anari

The supply side of Texas’ housing market is more flexible than the nation’s as well as California’s and New York’s. Currently, the state’s housing supply is in the growing phase of a construction cycle that began after the recovery from the Great Recession of 2007–09.

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experienced five cycles since 1970. Finally, although there is some comovement between Texas and U.S. home starts, the correlation is not strong.

The first Texas housing construction cycle reached a peak of 177,000 housing units in 1972 and ended in a trough of 108,400 in 1974. This cycle coincided with a U.S. housing construction cycle that peaked at 2,360,750 housing units in 1972. The second Texas housing construction cycle began in 1975 and lasted five years. It reached a peak of 217,000 units in 1977 and ended in a trough of 147,590 in 1980. The corresponding cycle for the nation lasted seven years, from 1975 to 1982, and reached a high of more than two million housing units in 1978.

Figure 1 Housing Starts, Texas and U.S., in Thousands

2,500 2,000

400

United States

300

(right axis)

200

Texas

1,500 1,000 500

(left axis)

100

0 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 Source: Haver Analytics

T

he Real Estate Center researched housing starts data from 1970 to 2015 to study the supply side of Texas housing markets. Housing starts are one of the leading economic indicators for local economies because buying a new house normally boosts consumer expenditures on appliances, furniture, and other home-related items.

Texas and U.S. Housing Starts History and Cycles Time series of housing starts for both the United States and Texas reveal several common features (Figure 1). First, housing starts for both the U.S. and Texas have proceeded in cycles of expansion followed by contraction. Second, no two housing start cycles were quite the same in duration or amplitude.

Third, the supply sides of the Texas and U.S. housing markets APRIL 2016

Oil prices as high as $40 per barrel fueled Texas’ third housing construction cycle, which began in 1981 and peaked at 298,550 housing units in 1983. After that, oil prices collapsed, causing housing construction to fall by 85 percent to a trough of 42,250 units in 1988. This time the nation’s housing construction cycle lasted nine years, from 1982 to 1991, and reached a peak of 1,812,000 units in 1986.

From 1989 the supply side of the state’s housing market began its fourth housing starts cycle, characterized by a long and slow upward trend. The cycle reached a peak of 212,000 units in 2006, just before the onslaught of the Great Recession, but was still lower than the all-time high of 298,550 in the previous cycle. uring the Great Recession, the state’s housing construction fell 62.5 percent to 79,550 in 2009. The nation’s fourth housing construction cycle began in 1991, reached a peak of 2,072,900 units in 2005, then fell 73.3 percent to 554,000 units in the Great Recession. Since 2010, the housing markets of both the U.S. and Texas have been recovering from the Great Recession and currently are in the expansion phase of their fifth housing starts cycle (Figure 1).

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The contrast between the gradual upward trend in the state’s housing construction in the fourth cycle (1989–2006) compared with the oil price driven boom-bust of the third cycle (1981–88) suggests that the state’s building industry may have learned an important lesson: not to get carried away by ups and downs of oil prices in the short run and instead focus on the long-term relationships between housing demand and population growth.

Housing Supply Flexibility

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opulation is the single most important determinant of demand for housing units given that all people need shelter. As population grows in a region, the region’s housing market must be able to supply more housing units; otherwise, higher housing demand leads to higher home prices.

One measure of housing supply flexibility for a region is the number of new housing units per thousand people (Figure 2).

Comparing Texas with the U.S. reveals that there were three distinct periods of relative housing supply flexibility. New housing units per 1,000 people in Texas exceeded that of the nation from 1970 to 1985, reaching an all-time peak of 19 in 1983 compared with 7.3 for the U.S. in the same year. From 1986 to 1994 the state’s number of new homes per 1,000 people lagged that of the nation and fell to a trough of 2.5 in 1988 compared with six for the U.S.

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Figure 2 New Housing Units Per 1,000 People

periods of relative housing supply flexibility measured in terms of the share of new housing units (Figure 3). Texas’ share exceeded that of the nation until 1985 and reached an all-time peak of 4.9 percent in 1983 compared with 1.9 percent for the U.S. in the same year. From 1986 to 1994, the state’s share of new homes lagged behind that of the nation and fell to a trough of 0.6 percent in 1988 compared with 1.5 percent for the U.S. ince 1994 the share of new housing units in Texas has exceeded the corresponding share for the nation, reaching a pre-Great Recession peak of 2.3 percent in 2006. The pre-Great Recession peak of 1.7 percent for the U.S. occurred one year earlier, in 2005. During the Great Recession, this metric fell to 0.8 percent for Texas and 0.4 percent for the U.S. Since the U.S. economy’s recovery from the Great Recession, the percentages of new housing units for both the nation and Texas have been rising, but Texas has managed to attain higher shares of new homes (Figure 3).

S

Figure 3 Percent of New Housing Units

5 4

Texas

3 2 1

United States

0 1980

Texas

1985

1990

1995

2000

2005

2010 2014

Sources: Haver Analytics and Real Estate Center at Texas A&M University

10 5

Texas vs. California and New York United States

0 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 Sources: Haver Analytics and Real Estate Center at Texas A&M University

Since 1995 the Texas housing market has been able to supply more new homes per 1,000 people compared with the national average, reaching a pre-Great Recession peak of 9.1 in 2006.

The pre-Great Recession peak of seven for the U.S. occurred one year earlier in 2005. This metric fell to 3.2 for Texas and 1.8 for the U.S. during the Great Recession. Since the U.S. economy recovered from the Great Recession, numbers of new housing units for both the nation and Texas have been rising, but Texas has managed to produce more new housing units per 1,000 people (Figure 2).

Another metric of the flexibility of housing supply is the share of total housing units accounted for by new housing units. This metric indicates the ability of the supply side of a region’s housing market to add new homes or replace older homes. The higher the percentage of new housing units in housing stocks, the shorter the time to replace older homes.

Comparing Texas with the U.S., there were three distinct

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Since 1992, the number of new housing units per 1,000 people for Texas has exceeded those for California and New York (Figure 4). Since the post-Great Recession recovery, the gaps between the number of new housing units for Texas and the other two states have been widening, showing the higher flexibility of the supply side of the Texas housing market.

These findings are also supported by the shares of new homes in total housing stocks for Texas, California, and New York (Figure 5).

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Figure 4 New Housing Units, Per 1,000 Population Texas California New York

10 5 0 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 Sources: Haver Analytics and Real Estate Center at Texas A&M University TIERRA GRANDE

ROADS ARE BEING BUILT for a residential subdivision in south College Station. Availability of land gives Texas an advantage over California and New York.

Figure 6 Home Price Indexes, 1975=100

Housing Supply Flexibility and Home Prices The outcome of higher flexibility of the supply side of the Texas housing market is a mild long-term upward trend in Texas average home prices, mainly due to the general level of inflation as shown by home price indexes of the Federal Housing Finance Agency (Figure 6). Texas’ housing market has been able to respond to higher demand for housing units by supplying more homes while short-run supply and demand imbalances have generated wild fluctuations in home prices in California and New York (Figure 6).

Figure 5 Percent of New Housing Units

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Texas California New York United States

1,200 800 400 0 1975

1980

1985

1990

1995

2000

2005

2010

2015

Sources: Haver Analytics and Real Estate Center at Texas A&M University

housing supply bubble, which may be avoided in the current phase of the state’s housing supply as long as the state’s building industry has not forgotten the painful lessons learned in the turbulent 1980s.

Texas California New York

4

1,600

3

Dr. Anari (m-anari@tamu.edu) is a research economist with the Real Estate Center at Texas A&M University.

2 1 1980

1985

1990

1995

2000

2005

2010 2014

Sources: Haver Analytics and Real Estate Center at Texas A&M University

The relative ease of Texas’ land acquisition process and abundant supplies of land have been important factors contributing to the flexibility of the state’s housing supply, reducing the risk of a home price bubble followed by a major home price collapse.

But the housing supply flexibility has brought the risk of a APRIL 2016

THE TAKEAWAY Real Estate Center research revealed that Texas’ housing market is more flexible than California’s, New York’s, and the nation’s as a whole. Texas’ abundance of available land and the relative ease of acquiring it are key to the housing market’s flexibility.

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Commercial

Nonresidential Construction and the Texas Business Cycle

By Luis B. Torres and Harold D. Hunt

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C

ycles of over- and undersupply in commercial real estate (CRE) have occurred on numerous occasions. In the 1980s, commercial construction boomed in Texas, fueled by oil prices and tax laws, resulting in a massive oversupply of commercial space. This created serious problems for financial institutions.

Construction of commercial buildings, particularly office buildings, has always been cyclical in nature. The lags between conception and completion pose a critical problem. Because buildings can take several years to complete, economic conditions when a commercial building is delivered may be quite different from those prevailing at the start. To gain perspective on current and future commercial real estate markets it is important to look at historical experience and analyze CRE alongside the business cycle.

Recently, concern has been rising about the health of the Texas commercial real estate market in the face of declining oil prices and their impact on the regional economy. Approximately 77 percent of total nonresidential construction values are concentrated in the Texas Triangle, which comprises the APRIL 2016

state’s major metropolitan statistical areas (MSAs): AustinRound Rock, Dallas-Fort Worth-Arlington (DFW), HoustonThe Woodlands-Sugar Land, and San Antonio-New Braunfels.

This article uses the term “commercial” to refer to total nonresidential construction, which includes a wide range of property types from office buildings to hotels, hospitals, and public sector development. The variations in regional industry mix can lead to different economic and commercial real estate market outcomes.

For example, the presence of a strong energy sector in the Houston MSA generates different expectations for nonresidential real estate compared with the Austin MSA, where a strong technology industry is prevalent. Even before the current decline in oil prices, some concerns about CRE oversupply in the Texas Triangle were emerging.

GOOGLE HAS SIGNED A LEASE for 200,000 square feet at the new Green Water Treatment Plant redevelopment on West 2nd Street in Austin.

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Until now, there have been no attempts to measure the ups and downs in local nonresidential construction to see if they match the timing of Texas’ overall business cycle. The amount and volatility of nonresidential construction make it an important sector in the overall growth of the state’s economy.

Commercial Real Estate Construction

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iven the relative volatility of commercial construction, the major peaks and troughs are identified along with Texas business cycle peaks by decade and major events, such as U.S. and Texas recessions and oil and housing booms (Tables 1–3). Values of new monthly construction—commercial and the subsectors of office, retail, and warehousing— are a good measure of current output in the CRE construction industry. Although it is a single variable, it is useful to identify the commercial construction cycle, as it is an important initial step in analyzing the ups and downs of the CRE sector. Indexing construction values in the figures allows for clearer and better comparisons over time and between geographic areas.

Commercial construction in Texas historically reached two major peaks, first in July 1981 and again in May 1985, driven primarily by oil prices and tax policy that granted investors large tax breaks for developing real estate. The result was a massive oversupply of commercial space that created serious financial problems for many real estate investors and financial institutions, leading to a major trough in January 1990.

The overhang of the boom-and-bust period during the 1980s led to slow growth in construction through the early 1990s.

The growth rate of Texas commercial construction accelerated during the mid 1990s, reaching a plateau in September 2001.

The national recession that began in March 2001, caused by the high-tech bust and the catastrophic events of 9/11, carried

the United States and the Texas economy into recession and again slowed commercial construction, registering a trough in September 2002.

Even though the U.S. economy emerged from its downturn in 2002, the Texas economy remained weak until June 2003.

This caused a slow recovery in commercial construction until the end of 2005, when it accelerated, reaching a historic peak in June 2008.

As the financial crisis cast a shadow over commercial real estate, the following three years saw demand for office, retail, and warehouse space wither, increasing vacancy rates and lowering rents. The lack of commercial real estate lending paralleled the residential market. As a result, commercial construction dropped sharply, reaching a trough in December 2011.

In the aftermath of the Great Recession, the Texas economy outperformed the nation, primarily due to strong energy and technology sectors. This led to a recovery in commercial construction that peaked in December 2014, about the time oil prices began their sharp decline. The slowdown of the Texas economy caused the rate of commercial construction to decline during 2015. ommercial construction volatility by major Texas MSA varies with the size and diversity of the local economy.

This becomes obvious when comparing commercial construction at the state level to the major MSAs. Significant volatility differences exist between the state and the major markets as well as among the major markets themselves. Austin and San Antonio display more volatility than Houston and DFW given the smaller size of their economies. Austin’s economy remains largely driven by technology and state government, while the Houston economy remains a global energy center.

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Table 1. Chronology of Texas Office Construction Peaks and Troughs Compared to the Texas Business Cycle Region/MSA Texas

Peak Date

Lead (+)/Lag (-)

Business Cycle-Nonresidential

Trough Date

Lead (+)/Lag (-)

Business Cycle-Nonresidential

February 82 – September 81 October 85 – May 85 March 01 – July 98 June 08 – February 08

(+)5 (+)5 (+)32 (+)5

March 83 – January 84 Jan 87 – August 89 June 03 – December 03 November 09 – April 10

(-)10 (-)31 (-)7 (-)6

November 85 – May 85 November 00 – September 00 May 08 – November 06

(+)6 (+)2 (+)18

November 87 – April 91 March 03 – November 03 September 09 – April 10

(-)41 (-)8 (-)7

September 81 March 86 – January 85 March 01 – June 98 May 08 – December 06

(+)14 (+)33 (+)17

September 82 June 87 – June 92 March 03 – February 04 September 09 – August 10

(-)60 (-)11 (-)11

March 82 – November 81 May 01 – June 01 August 08 – March 08

(+)4 (-)1 (+)5

October 83 – December 96 July 03 – March 04 December 09 – February 10

(-)158 (-)8 (-)2

April 86 – February 84 June 01 – August 00 June 08 – November 07

(+)26 (+)10 (+)7

September 87 – June 90 May 03 – February 03 October 09 – January 12

(-)33 (+)2 (-)27

Austin

Dallas/Fort Worth

Houston

San Antonio

Notes: Estimated by Real Estate Center at Texas A&M University.

Sources: Dodge Data and Analytics, Dallas Federal Reserve Bank, and Real Estate Center at Texas A&M University

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Table 2. Chronology of Texas Retail Construction Peaks and Troughs Compared to the Texas Business Cycle Region/MSA Texas

Peak Date

Lead (+)/Lag (-)

Business Cycle-Nonresidential

Trough Date

Lead (+)/Lag (-)

Business Cycle-Nonresidential

February 82 – September 80 October 85 – July 85 March 01 – May 99 June 08 – January 07

(+)17 (+)3 (+)22 (+)17

March 83 – February 82 Jan 87 – November 89 June 03 – February 02 November 09 – July 10

(+)13 (-)34 (+)16 (-)8

July 80 November 85 – May 85 November 00 – September 00 May 08 – November 06

(+)6 (+)2 (+)18

November 82 November 87 – August 90 March 03 – October 03 September 09 – June 10

(-)33 (-)7 (-)9

October 80 March 86 – June 85 March 01 – March 99 May 08 – February 07

(+)9 (+)24 (+)45

May 82 June 87 – January 90 March 03 – November 03 September 09 – December 09

(-)31 (-)8 (-)3

March 82 – January 80 November 84 – May 85 May 01 – July 01 August 08 – May 07

(+)26 (-)6 (-)2 (+)15

October 83 – November 81 December 86 – January 87 July 03 – July 05 December 09 – January 10

(+)23 (-)1 (-)24 (-)1

September 80 April 86 – July 84 June 01 – November 00 June 08 – August 05

(+)21 (+)7 (+)34

July 81 September 87 – November 89 May 03 – December 03 October 09 – February 11

(-)26 (-)7 (-)16

Austin

Dallas/Fort Worth

Houston

San Antonio

Notes: Estimated by Real Estate Center at Texas A&M University.

Sources: Dodge Data and Analytics, Dallas Federal Reserve Bank, and Real Estate Center at Texas A&M University

Table 3. Chronology of Texas Warehouse Construction Peaks and Troughs Compared to the Texas Business Cycle Region/MSA Texas

Peak Date

Lead (+)/Lag (-)

Business Cycle-Nonresidential February 82 – April 81 October 85 – September 85 December 96 March 01 – January 01 June 08 – June 07

Trough Date

Lead (+)/Lag (-)

Business Cycle-Nonresidential (+) 10 (+)1 (+)2 (+)12

March 83 – May 83 Jan 87 – April 93 September 97 June 03 – July 04 November 09 – October 10

(-)2 (-)75 (-)13 (-)13

Austin June 81 November 85 – October 85 May 95 November 00 – March 99 May 08 – June 08

(+)1 (+)20 (-)1

March 82 November 87 – May 92 April 96 March 03 – June 06 September 09 – May 09

(-)54 (-)39 (+)4

Dallas/Fort Worth January 80 March 86 – October 85 December 96 March 01 – November 00 May 08 – April 07

(+)4 (+)13

November 82 June 87 – October 92 October 97 March 03 – February 04 September 09 – October 10

(-)11 (-)13

March 82 – March 81 November 84 – March 85 May 01 – June 01 August 08 – June 08

(+)12 (-)4 (-)1 (+)2

October 83 – October 83 December 86 – January 87 July 03 – July 05 December 09 – January 10

(-)1 (-)24 (-)1

April 86 – December 85 September 91 June 01 – May 98 June 08 – October 07

(+)4

September 87 – October 90 September 93 May 03 – April 02 October 09 – February 11

(+)5

(-)64

Houston

San Antonio

(+)37 (+)8

(-)37 (+)13 (-)40

Notes: Estimated by Real Estate Center at Texas A&M University.

Sources: Dodge Data and Analytics, Dallas Federal Reserve Bank, and Real Estate Center at Texas A&M University APRIL 2016

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In contrast, the DFW economy is more highly correlated to the U.S. economy. San Antonio depends heavily on tourism and federal government employment, mainly through local military bases and a wide variety of private and public entities that support them.

Ups and Downs in Nonresidential Commercial Construction

T

Recession for DFW was March 2008. Houston peaked three months later, in June 2008.

The largest San Antonio peak occurred in August 2007 at the end of the housing boom, followed by another in August 2014, as a prelude to the fall in oil prices.

Not surprisingly the lowest troughs in total nonresidential construction were registered during the 1980s and early 1990s in the aftermath of the oil bust. Houston and San Antonio reached their lowest troughs in June 1986 and December 1989, respectively; the state in January 1990; and Austin and DFW in October 1990 and September 1992, respectively.

Further commercial construction analysis segments the major MSAs by office buildings, retail structures and warehouses, which account for about 50 percent of the value of all private nonresidential construction from January 1980 to November 2015.

he differences in the composition of the four major Texas MSAs resulted in differences in local growth rates in total nonresidential construction. Austin registered the biggest average annual inflation-adjusted growth rate of 13.7 percent from January 1981 to November 2015, followed by San Antonio with 6.7 percent. Houston and DFW registered 4.6 percent and 4.0 percent annual growth, respectively. The state registered an average annual growth rate of 2.6 percent (Table Office Construction 4). Together, the four MSAs produced, on average, 73.4 percent In the case of office construction, Texas and the major MSAs of all commercial construction in Texas between January 1980 achieved their maximum peaks in the early 1980s, primarily as and November 2015. DFW’s share of new total nonresidential a result of the oil boom. construction is 32.8 percent, followed by Houston with 24.8 The lowest troughs percent, San Antonio for office construction with 8.5 percent, and Table 4. Nonresidential Inflation Adjusted Annual were registered in the Austin with 7.2 percent.

Growth Rates by Property Type aftermath of the Great Major peaks and January 1981 to November 2015 Recession in April 2010 troughs in commercial in both Texas and Ausconstruction reflect Region/MSA Nonresidential Office Retail Warehouse tin, and in August 2010 differences in local Texas 2.6 4.1 3.2 8.1 in DFW. In contrast, San construction cycles.

Austin 13.7 22.4 19.7 40.2 Antonio and Houston After reaching a small DFW 4.0 8.7 6.1 25.5 recorded their lowest peak in 1983, Austin Houston 4.6 16.5 6.7 15.5 troughs in June 1990 had its first major peak San Antonio 6.7 16.3 12.9 52.3 and December 1996, as in construction activity Notes: Seasonally adjusted and detrended. Estimated by Real Estate Center at Texas A&M University. an oversupply of office in April 1985, coincidSource: Dodge Data and Analytics space from the oil bust ing with the state’s oil was still being felt. boom. The MSA’s largAustin recorded the largest office construction growth rate est peak occurred in December 2014. in real terms from January 1981 to November 2015, an average In contrast, DFW and Houston reached major peaks in June annualized rate of 22.4 percent. Houston followed with 16.5 1985 and October 1981, respectively, during the unprecedented percent, San Antonio at 16.3 percent, and finally DFW with 8.7 expansion in commercial real estate fueled by the 1980s oil percent. The major MSA growth rates are greater than the state’s boom and distorted federal tax laws. The peak before the Great 4.1 percent (Table 5) but with greater volatility (Tables 6 and 7).

Table 5. Nonresidential Volatility in Annual Growth Houston surprisingly registers the highest volaRates by Property Type vs. Texas tility, followed by Austin, San Antonio, and DFW, January 1981 to November 2015 which registers the lowest volatility (Table 6). In Region/MSA Nonresidential Office Retail Warehouse this regard, higher growth rates are accompanied by greater volatility in the office market. These four Texas 1.0 1.0 1.0 1.0 MSAs represent 82.2 percent of the new private office Austin 6.4 4.3 12.7 9.2 construction in Texas between January 1980 and DFW 2.1 1.6 2.1 5.2 November 2015. DFW’s share of new office construcHouston 2.5 5.9 2.3 2.5 tion is 39.2 percent, followed by Houston with 27.3 San Antonio 2.9 3.4 5.4 14.5 percent, Austin with 8.8 percent, and San Antonio Notes: Seasonally adjusted and detrended. Estimated by Real Estate Center at Texas A&M University.

Source: Dodge Data and Analytics with 6.8 percent.

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DALLAS CONSTRUCTION showed fewer ups and downs and a more stable growth rate than the other major MSAs.

Retail Construction

N

ew retail construction in the state and DFW reached its maximum peak in July 1985 and June 1985, respectively, around the oil boom. Austin and San Antonio achieved maximum peaks in the later stages of the housing boom, in September 2006 and August 2005. Surprisingly, Houston reached its maximum retail construction peak during the U.S. and Texas recession of 2001.

Like total nonresidential construction, new retail construction reached its trough in the 1980s and early 1990s. Both San Antonio and Austin recorded their lowest troughs in July 1981 APRIL 2016

and November 1982. The state and DFW reached their troughs in November 1989 and January 1990, after Houston had registered its low point in January 1987.

Austin registered the highest annual retail construction inflation-adjusted growth rate, 19.7 percent, between January 1981 and November 2015 followed by San Antonio with 12.9 percent, Houston with 6.7 percent, and DFW with 6.1 percent. The state recorded a 3.2 percent annual average growth rate (Table 5). Again, the relationship between growth rates and volatility is present as in retail construction. Surprisingly, DFW’s volatility is slightly lower than that of Houston (Table 6), which registered similar growth rates. The four major MSAs represented 70.8 percent of all new private retail construction in the state between January 1980 and November 2015. DFW’s share of new retail construction was 31.7 percent, followed by Houston with 23.6 percent, San Antonio with 8.5 percent, and Austin with 7.1 percent.

Warehouse Construction Before the Great Recession, new warehouse construction in Texas recorded its maximum peak in June 2007. Similarly, San Antonio reached its maximum peak in October 2007, in contrast to Houston and Austin, which peaked at the

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start and the end of the oil boom, in March 1981 and September 1985, respectively. DFW reached its maximum peak at the end of the tech boom in November 2000 that gave way to the U.S. and Texas recessions of 2001.

Commercial Residential Construction and the Business Cycle

The volatility in commercial construction activity makes it difficult to clearly identify construction cycles. However, major construction peaks and troughs generally Table 6. Nonresidential Volatility in Annual Growth occur around major economic events such as recesRates by Property Type vs. Nonresidential sions and periods of boom and bust. All these peaks January 1981 to November 2015 and troughs share periods of expansion driven by external shocks from factors such as oil prices in Region/MSA Nonresidential Office Retail Warehouse addition to economic fundamentals such as employTexas 1.0 3.7 1.6 4.9 ment growth in business and financial services. Just Austin 1.0 2.5 3.1 7.0 like the overall business cycle in Texas, each comDFW 1.0 2.8 1.5 11.9 mercial construction cycle is different from previous Houston 1.0 8.8 1.5 4.9 ones because different economic factors affect the San Antonio 1.0 4.3 2.9 24.3 duration of expansion and contractions. As Tables Notes: Seasonally adjusted and detrended. Estimated by Real Estate Center at Texas A&M University.

1–4 show, there is no set time pattern on the duraSource: Dodge Data and Analytics tion of business cycles as each business cycle has distinct factors in play besides common characteristics that can lead to a turning point.

The state and the Texas Triangle MSAs, with the excepThe Texas coincident business cycle index estimated by the tion of San Antonio, reached their lowest point in warehouse Federal Reserve Bank of Dallas provides a basis to compare construction activity during the 1990s as the state still felt the differences in the turning points of the Texas economy and effects of the 1980s oil bust. Austin and DFW reached their CRE construction. It’s possible that a slowdown in commertroughs in May and October 1992, respectively, while the state cial construction affects the outlook of the general economy. and Houston fell to their lowest points in March 1993 and Interestingly, Table 1 shows that nonresidential construction September 1996. San Antonio did not reach its trough until peaks often lead the overall Texas economic business cycle, February 2011 in the aftermath of the Great Recession. while the troughs consistently lag. Residential construction he largest average real annual growth rate in new also leads the Texas business cycle, influencing the state’s ecowarehouse construction was registered by San Antonio nomic expansions and contractions and not conforming with at 52.3 percent from January 1981 to November 2015, followed by Austin with 40.2 percent, DFW with 25.5 percent, Table 7. Chronology of Texas Nonresidential Construction Peaks and Troughs Houston with 15.5 percent, and Compared to the Residential Business Cycle the state with 8.1 percent (Table 4). Once again, the relationship Peak Date Lead (+)/Lag (-) Trough Date Lead (+)/Lag (-) between high growth rates and Residential - Nonresidential Residential - Nonresidential high volatility is present (Table September 79 – July 81 (-)22 August 82 – October 83 (-)14 5). Between January 1980 and May 84 – May 85 (-)12 March 89 – Jan 90 (-)10 November 2015, 75.7 percent September 01 September 02 of all growth in the state’s new January 2007 – June 08 (-)17 June 11 – December 11 (-)6 warehouse construction was concentrated in the major MSAs. Notes: Estimated by Real Estate Center at Texas A&M University.

Sources: Dodge Data and Analytics, Dallas Federal Reserve Bank, and Real Estate Center at Texas A&M University DFW’s share of new warehouse construction was 40.8 percent, the timing of the turning points in the overall Texas economy. followed by Houston with 24.8 percent, San Antonio with 6.2 Another difference is the duration of expansions and contracpercent, and Austin with 3.8 percent. tions as expansions are shorter and contractions last longer on When comparing the volatility by property type in comaverage compared with the Texas business cycle. Still, surprisparison to total nonresidential, the most volatile property ingly, no causal statistical relationship was found between type in general is warehouse followed by office and then by the business cycle and nonresidential construction due to the retail (Table 6). There are exceptions like Houston, in which volatility in the construction data. the most volatile property type is office followed by wareA further comparison was conducted using the residential house, and Austin, where office registers the lowest conbusiness cycle determined by the Real Estate Center at Texas struction variance.

T

12

TIERRA GRANDE

AUSTIN’S CENTRAL BUSINESS district is hosting a flock of cranes, including this one at 5th and Colorado.

A&M University and the residential construction index estimated by the Federal Reserve Bank of Dallas and the Center.

The comparison revealed that nonresidential construction lags both the peaks and troughs in residential construction (Table 7). In addition, nonresidential construction follows more closely the overall Texas business cycle than residential construction. This highlights the differences between residential and nonresidential construction, the unevenness and volatility of CRE compared with residential construction and how housing leads the overall business cycle in the economy.

Concluding Remarks

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onresidential construction in Texas and all four major MSAs declined during 2015 in conjunction with the general slowdown of the Texas economy. This is not surprising because every downturn in state nonresidential construction has been accompanied by a recession or the end of a boom and bust period that has generally lagged the construction cycle. In addition, all nonresidential construction cycles were dissimilar from previous ones due to differing economic conditions. It is too early to tell if the business cycle decline as an overall trend will continue in 2016, but early evidence confirms the Texas economy is slowing.

Construction of new office space in the state, Austin, and especially Houston has also declined during 2015. New retail construction has been mixed, while the state, Dallas, and Houston recorded an uptick during the majority of 2015 and then slowed at the end of year. This contrasts with Austin and San Antonio, where activity slowed during the year. Warehouse construction at the state level decreased during the first APRIL 2016

half of 2015, then experienced growth for the rest of the year.

Austin warehouse construction is growing in contrast to DFW, Houston, and San Antonio, where construction fell in 2015.

The Texas nonresidential construction cycle differed from the state business cycle and residential construction cycles. Nonresidential construction leads the Texas economy’s peaks, and lags its troughs while consistently lagging the turning points of residential construction. This demonstrates the inherent differences between construction and market business cycles.

The next step will be to look at other variables that may help indicate the turning points in the nonresidential construction business cycle. Once those are identified, researchers can construct a coincident indicator for nonresidential construction to mark precise peaks and troughs in the cycle and thus the timing and length of expansions and recessions. Such an indicator would resemble the residential construction business cycle estimated by the Federal Reserve Bank of Dallas and the Real Estate Center.

This article is available with additional tables and graphs on the Real Estate Center website at recenter.tamu.edu.

Dr. Torres (ltorres@mays.tamu.edu) and Dr. Hunt (hhunt@tamu.edu) are research economists with the Real Estate Center at Texas A&M University.

THE TAKEAWAY The nonresidential construction cycle is different from the Texas economy’s peaks and troughs. This research is the first step in defining the turning points in nonresidential construction.

13

Water

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TIERRA GRANDE

I

In the late 1800s, officials of Los Angeles, California, realized water availability would limit the growth of the city to a maximum population of 250,000. They solved that problem by undertaking what was then the world’s most ambitious engineering project—the Los Angeles Aqueduct—designed to

APRIL 2016

By Charles E. Gilliland

secure future water supplies for the expanding city.

Now, lack of water looms as the ultimate limiting constraint to further growth in Texas. Many Texans fear that no one is planning to address those future shortfalls. However, Texas actually is at the forefront when it comes to systematically

15

preparing to meet water demand in the future. Even so, challenges lie ahead as the state struggles to define and refine a legal infrastructure to resolve the issue of shortages.

To ensure water supplies, Texas legislators have devised an evolving water-planning process. Originating with local entities, the effort produces an updated statewide water plan that peers 50 years into the future every five years. Those plans estimate future demands for water, identify currently available supplies from specific sources, and forecast special needs (situations in which demands exceed supplies available during a drought of record). The plans then offer a menu of strategies to eliminate those needs. Local entities must allocate and augment existing water supplies to accomplish ends envisioned in the strategies. lthough parts of Texas have abundant surface water supplies, a provision in the Texas Water Code (TWC) designed to protect permit holders in each river basin makes it unlikely that surface supplies will play a significant role in dealing with shortages. Most of the strategies focus on prudent development and use of groundwater supplies. Locally controlled groundwater conservation districts (GCDs) play a pivotal role in the ongoing planning process. Texans concerned about water in the future should learn about the planning process and the important role assigned to GCDs to guide the fortunes of Texas.

GCDs are political subdivisions of the State of Texas designed to “. . . provide for conservation, preservation, protection, recharging, and prevention of waste of groundwater . . . and to control subsidence . . .” (Texas Water Code 36.0015). To accomplish that mission, each GCD operates under a board of directors consisting of at least five members. GCDs can make rules governing water usage designed to accomplish goals developed in the water planning process subject to landowners’ groundwater property rights. However, because they are under the jurisdiction of the Texas Water Development Board (TWDB) and the Texas Commission on Environmental Quality, GCDs do not operate entirely autonomously. eginning with the High Plains Underground Water Conservation District No. 1 in 1951, the current roster includes 99 districts, one of which is pending voter confirmation. The districts cover parts of 177 counties with 61 of those covering only one county and 39 extending over more than one county (Figure 1). All colored areas lie within a GCD while the white areas do not. Clearly, much of Texas is under the control of a GCD. However, many district boundaries lie largely along political lines while aquifers managed by GCD rules do not. Obviously, a patchwork of GCDs with independent boards guided by local whims could create a chaotic stew of rules reflecting varied visions of sensible water management.

Attempting to achieve some consistency in management over shared aquifers, the water code specifies that all GCDs within a designated Groundwater Management Area (GMA) must meet to identify the desired future conditions (DFC) for each aquifer lying beneath those districts. As the GMA map reveals, GMA boundaries enclose multiple counties and outline all or parts of the major aquifers in Texas (Figure 2). Once every five years the GCDs included in each GMA must meet to establish DFC for each aquifer in the GMA. Two-thirds of

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DALLAM

Confirmed Groundwater Conservation Districts *

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WHEELER

Figure 1 Groundwater Conservation Districts of Texas

MORRIS

FRANKLIN

1. Bandera County River Authority & Ground Water District - 11/7/1989 64 2. Barton Springs/Edwards Aquifer CD - 8/13/1987 DEAF SMITH RANDALL ARMDONLEY COLLINGSSTRONG WORTH 3. Bee GCD - 1/20/2001 4. Blanco-Pedernales GCD - 1/23/2001 56 CHIL5. Bluebonnet GCD - 11/5/2002 PARMER CASTRO SWISHER BRISCOE HALL DRESS 6. Brazoria County GCD - 11/8/2005 HARDE37 7. Brazos Valley GCD - 11/5/2002 28 MAN WILBARBAILEY LAMB HALE FLOYD MOTLEY 8. Brewster County GCD - 11/6/2001 WICHITA COTTLE FOARD GER 9. Brush Country GCD - 11/3/2009 10. Calhoun County GCD - 11/4/2014 COCH- HOCKLEY LUBBOCK CROSBY DICKENS KING KNOX BAYLOR ARCHER CLAY MONTA- COOKE GRAYSON FANNIN LAMAR RED RIVER GUE RAN 11. Central Texas GCD - 9/24/2005 75 DELTA BOWIE 79 62 12. Clear Fork GCD - 11/5/2002 YOAKUM TERRY GARZA STONETHROCK- YOUNG WISE LYNN TITUS HASKELL HUNT HOPKINS KENT COLLIN JACK WALL 13. Clearwater UWCD - 8/21/1999 MORTON CASS DENTON 82 85 27 14. Coastal Bend GCD - 11/6/2001 94 TARRANT ROCKCAMP RAINS GAINES DAWSON FISHER WALL WOOD MARION 15. Coastal Plains GCD - 11/6/2001 JONES SHACKLE- STEPHENS PALO PARKER BORDEN SCURRY UPSHUR PINTO FORD 63 DALLAS KAUF47 55 VAN 16. Coke County UWCD - 11/4/1986 12 MAN ZANDT HARRISON GREGG 17. Colorado County GCD - 11/6/2007 HOOD JOHNSON ELLIS MARTIN HOWARD MITCHELL NOLAN ERATH TAYLOR CALLA- EASTLAND ANDREWS HAN 18. Comal Trinity GCD - 6/17/2015 HENDERSON SMITH RUSK PANOLA 72 SOMER67 49 97 VELL 19. Corpus Christi ASRCD - 6/17/2005 NAVARRO 80 65 GLASS- STERCOKE HILL 60 BOSQUE COMAN20. Cow Creek GCD - 11/5/2002 LING EL PASO LOVING WINKLER ECTOR MIDLAND COCK CHE CHEROSHELBY 39 RUNNELS COLEMAN ANDER- KEE 59 FREEBROWN NACOG21. Crockett County GCD - 1/26/1991 29 89 16 SON HAMILTON STONE DOCHES MCLENNAN WARD 22. Culberson County GCD - 5/2/1998 MILLS CRANE 45 87 IRION 57 HOUSTON 68 UPTON REAGAN HUDSPETH CULBERSON 23. Duval County GCD - 7/25/2009 TOM CORYELL CONCHO REEVES LEON MCCULFALLS 24. Edwards Aquifer Authority - 7/28/1996 83 40 GREEN LOCH SAN SABA 84 BELL ROBERTTRINITY 77 22 25. Evergreen UWCD - 8/30/1965 SON SCHLEICHER MENARD 36 MADISON 13 BURNET POLK PECOS 26. Fayette County GCD - 11/6/2001 JEFF DAVIS MILAM CROCKETT 7 MASON LLANO 69 54 11 WALKER 51 TYLER86 27. Garza County UWCD - 11/5/1996 WILLIAMSON SAN 58 71 41 KIMBLE SUTTON 21 JACINTO 28. Gateway GCD - 5/3/2003 BURLESON MONTHARDIN GILLESPIE 43 LEE 90 TERRELL ORANGE 4 TRAVIS 29. Glasscock GCD - 8/22/1981 5 GOMERY WASHING38 50 48 TON 30. Goliad County GCD - 11/6/2001 PRESIDIO 33 VAL VERDE 34 2 BASTROP EDWARDS LIBERTY 91 HAYS KERR KENDALL 31. Gonzales County UWCD - 11/2/1994 FAYETTE AUSTIN BREWSTER 73 A HARRIS CHAMBERS 74 REAL BANDERA 20 COMAL CA70 LDWEL 32. Guadalupe County GCD - 11/14/1999 L 26 COLORADO 1 93 18 33. Hays Trinity GCD - 5/3/2003 8 FORT GUADALUPE GONKINNEY MEDINA UVALDE BEXAR 3231ZALES LAVACA 17 BBEND 34. Headwaters GCD - 11/5/1991 N TO WHARTON ES 44 95 53 24 WILSON DE WITT 35. Hemphill County UWCD - 11/4/1997 LV 14 BRAZORIA GA 6 36. Hickory UWCD No. 1 - 8/14/1982 ZAVALA 15 25 KARNES 66 37. High Plains UWCD No.1 - 9/29/1951 FRIO 92 MATAGORDA ATASCOSA GOLIAD 38. Hill Country UWCD - 8/8/1987 96 98 MCBEE 30 39. Hudspeth County UWCD No. 1 - 10/5/1957 10 DIMMIT MULLEN REFUGIO LA SALLE 40. Irion County WCD - 8/2/1985 3 78 UN 76. Red Sands GCD - 11/5/2002 46 LHO SAN 52 CA 41. Jeff Davis County UWCD - 11/2/1993 PATRICIO 77. Reeves County GCD - 11/3/2015 42. Kenedy County GCD - 11/2/2004 81 99 DUVAL 78. Refugio GCD - 11/6/2001 43. Kimble County GCD - 5/3/2002 WEBB 79. Rolling Plains GCD - 1/26/1999 NUECES 44. Kinney County GCD - 1/12/2002 23 KLEBERG 19 80. Rusk County GCD - 6/5/2004 45. Lipan-Kickapoo WCD - 11/3/1987 81. San Patricio County GCD - 5/12/2007 46. Live Oak UWCD - 11/7/1989 TEXAS WATER DEVELOPMENT BOARD 82. Sandy Land UWCD - 11/7/1989 9 ZAPATA 42 47. Llano Estacado UWCD - 11/3/1998 JIM 83. Santa Rita UWCD - 8/19/1989 1700 North Congress Avenue | P.O. Box 13231 HOGG BROOKS KENEDY 48. Lone Star GCD - 11/6/2001 84. Saratoga UWCD - 11/7/1989 Austin, Texas 78711-3231 STARR 49. Lone Wolf GCD - 2/2/2002 85. South Plains UWCD - 2/8/1992 www.twdb.texas.gov 50. Lost Pines GCD - 11/5/2002 88 76 WILLACY 86. Southeast Texas GCD - 11/2/2004 51. Lower Trinity GCD - 11/7/2006 HIDALGO 87. Southern Trinity GCD - 6/19/2009 CAMERON 52. McMullen GCD - 11/6/2001 88. Starr County GCD - 1/6/2007 53. Medina County GCD - 8/26/1991 89. Sterling County UWCD - 11/3/1987 54. Menard County UWD - 8/14/1999 90. Sutton County UWCD - 4/5/1986 55. Mesa UWCD - 1/20/1990 Confirmed districts are arranged in alphabetical order. Dates indicate when district 91. Terrell County GCD - 11/6/2012 56. Mesquite GCD - 11/4/1986 was established by law or election.

92. Texana GCD - 11/6/2001 57. Mid-East Texas GCD - 11/5/2002 93. Trinity Glen Rose GCD - 11/5/2002 58. Middle Pecos GCD - 11/5/2002 * Districts that have, in whole or part, authority as assigned by Chapter 36 of the 94. Upper Trinity GCD - 11/6/2007 59. Middle Trinity GCD - 5/4/2002 Texas Water Code. Please refer questions pertaining to individual districts to the 95. Uvalde County UWCD - 9/1/1993 60. Neches & Trinity Valleys GCD - 11/6/2001 districts themselves. (http://www.twdb.state.tx.us/groundwater/conservation_districts) 96. Victoria County GCD - 8/5/2005 61. North Plains GCD - 1/2/1955 97. Wes-Tex GCD - 11/5/2002 ** The subsidence districts are not Groundwater Conservation Districts as defined 62. North Texas GCD - 12/1/2009 98. Wintergarden GCD - 1/17/1998 63. Northern Trinity GCD - 5/15/2007 under Chapter 36 of the Texas Water Code, but have the ability to regulate 64. Panhandle GCD - 1/21/1956 groundwater production to prevent land subsidence. (Senate Bill 1537 from the 79th Unconfirmed Groundwater Conservation Districts 65. Panola County GCD - 11/6/2007 Legislative Session).

99. Aransas County GCD + # 66. Pecan Valley GCD - 11/6/2001 67. Permian Basin UWCD - 9/21/1985 Groundwater Conservation District GIS Data created by the Texas Commission on + Pending Election Results 68. Pineywoods GCD - 11/6/2001 Environmental Quality. For more information, please contact TCEQ at 512-239-1000 # Created by the 84th Legislature 69. Plateau UWC and Supply District - 3/4/1974 or wras@tceq.texas.gov.

70. Plum Creek CD - 5/1/1993 Subsidence Districts ** DISCLAIMER: This map was generated by the Texas Water Development Board using 71. Post Oak Savannah GCD - 11/5/2002 A. Harris-Galveston Subsidence District 72. Prairielands GCD - 9/1/2009 GIS (Geographical Information System) software. No claims are made to the accuracy B. Fort Bend Subsidence District 73. Presidio County UWCD - 8/31/1999 or completeness of the information shown herein nor to its suitability for a particular 74. Real-Edwards C and R District - 5/30/1959 use. The scale and location of all mapped data are approximate. Map date: NOV-2015 County Boundaries 75. Red River GCD - 9/1/2009 A

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Groundwater Management Areas Pecos Valley Aquifer Seymour Aquifer Gulf Coast Aquifer Carrizo - Wilcox Aquifer (Outcrop) Carrizo - Wilcox Aquifer (Subcrop) Hueco - Mesilla Bolson Aquifer Ogallala Aquifer Edwards - Trinity (Plateau) Aquifer (Outcrop) Edwards - Trinity (Plateau) Aquifer (Subcrop) Edwards (Balcones Fault Zone) Aquifer (Outcrop) Edwards (Balcones Fault Zone) Aquifer (Subcrop) Trinity Aquifer (Outcrop) Trinity Aquifer (Subcrop)

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Figure 2 Major Aquifers of Texas with Groundwater Management Areas

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BROOKS JIM HOGG STARR HIDALGO

KENEDY WILLACY CAMERON

- Aquifer chronology by geologic age.

- Solid colors indicate OUTCROP areas (portion of a water-bearing rock unit exposed at the land surface).

- Hatch colored lines indicate SUBCROP areas (portion of a water-bearing rock unit existing below other rock units).

TEXAS WATER DEVELOPMENT BOARD 1700 North Congress Avenue | P.O. Box 13231 Austin, Texas 78711-3231 www.twdb.texas.gov

DISCLAIMER: This map was generated by the Texas Water Development Board using GIS (Geographical Information System) software. No claims are made to the accuracy or completeness of the information shown herein nor to its suitability for a particular use. The scale and location of all mapped data are approximate. Map date: JULY 2015

the districts in the GMA must approve those conditions. The districts then must forward a report including the DFC and addressing the required steps in the adoption process to the TWDB. The board then studies the DFC to make sure they are reasonable and feasible. Once the TWDB deems the DFC to be reasonable, the GCDs officially adopt them. Those DFC form the foundation for the individual management plans and rules adopted by each GCD. ithin 120 days after adoption, an affected stakeholder can file a petition with a GCD to object to the DFC. That district must then contract with the State Office of Administrative Hearings (SOAH) to have a hearing to evaluate the reasonableness of the DFC in question. The GCD notifies TWDB to initiate a prescribed response from the board to the SOAH. The process unfolds under the guidance of an administrative law judge who considers specific evidence to reach a verdict. If petitioners remain dissatisfied with the SOAH outcome, they can file suit in district court.

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Once established, GCDs must devise management plans to achieve the DFC in 50 years. Knowledge of the hydrology of the aquifers serves as the basis for groundwater availability models devised by TWDB to predict the total volume of water available in each aquifer. These hydrological model forecasts establish the modeled available groundwater (MAG) for each aquifer, and the GCD boards use the MAG estimates as they design rules that allocate water. Those rules must help to achieve the DFC established by the cooperative planning process. These action plans become part of the Regional Water Plan. Obviously, the official planning process differs from a perceived state-level, hands-off approach depending solely on Regional Water Planning Group decisions.

In fact, through the water code, the state does provide specific instructions that the local GCDs must observe as they discharge their duties. First, the code specifies that GCDs covered by the GMA must consider the following nine items as they devise DFC: TIERRA GRANDE

• aquifer uses or conditions, • water supply needs and strategies included in state water plan, • hydrological conditions, • • • • •

other environmental impacts, impact on subsidence, socioeconomic impacts, impact on private property rights (TWC 36.002),

feasibility of achieving desired future condition and • any other information relevant to specific desired future conditions (TWC 36.108). iven these concerns and requirements to address these in the GMA report, the GCDs consult with TWDB hydrologists employing models of water supplies that consider situations in each district for every managed aquifer.

Initially, GCDs approached rule making with few constraints. However, Texas Supreme Court rulings have cast a pall over GCDs’ planning and rule making (Edwards Aquifer Authority v. Day and McDaniel [Tex. 2012] and Edwards Aquifer Authority v. Bragg [San Antonio 2013]). The Day case affirmed landowners’ rights to the water located beneath their land and ruled denying access to that water constitutes a taking of property and requires compensation. The Bragg case argued for compensation based on a partial denial of a permit for water. The plaintiffs prevailed in both cases. Obviously, GCDs might devise rules that bar landowners from pumping their groundwater. However, if they do so, they are vulnerable to a lawsuit demanding compensation. Legal experts believe that GCDs that allocate water on a fair-share basis to all landowners in the district will likely avoid liability in takings cases. Only time will tell which rules will pass muster.

Finally, the map of GCDs still contains an abundance of white spaces representing areas entirely subject to the rule of capture. Those areas are not covered by GCD rules nor are they included in the water-planning process. However, landowners located in those rule-of-capture areas may find themselves subject to legal and political action when they attempt to undertake ambitious projects like the Electro Purification project in Hays County (see Center publication 2103, “Marketing Texas Groundwater”). Ultimately, the Texas Legislature passed a bill extending the boundaries of the Barton Springs Edwards Aquifer Conservation District to cover wells planned in a ruleof-capture “white” area.

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Dr. Gilliland (c-gilliland@tamu.edu) is a research economist with the Real Estate Center at Texas A&M University.

THE TAKEAWAY Texas is ahead of many other states in planning for future water supplies. Even so, many unanswered questions remain regarding groundwater regulation in the state.

APRIL 2016

19

Legal Issues

Glad You Asked

By Judon Fambrough

Questions from Readers

T

he article “Licensing Act Changes and More” that appeared in the January issue of Tierra Grande sparked questions and concerns from readers. This article addresses those inquiries.

Transfer on Death Deeds The majority of the inquiries were about Transfer on Death Deeds (TODD) found in Chapter 114 of the Texas Estates Code. The new statute recognizes for the first time a new type of deed in Texas. These deeds, once executed and recorded, do not transfer an immediate interest in real property. Instead, the transfer takes effect at the grantor’s death without the need of probate. In the interim, the grantor is free to revoke or change the deed without the consent of the grantee and without any legal consequences.

These deeds possess some aspects of a regular deed and some of jointly owned property with a right of survivorship. Property owners may use these deeds as a substitute for a will or even to remove assets that would otherwise pass under the terms of an existing will.

According to the statute, for a TODD to be effective, the deed must state explicitly that it takes effect at the grantor’s death.

(See Section 114.151 of the Texas Estates Code for a sample form.)

In all other ways, the deed must be executed with the same formalities as a regular deed and be recorded before the grantor’s death (see Center publication 2116, “2015 Legislative Changes”).

Attorney and title companies question whether TODDs comply with the same formalities as a regular deed. Here is why. For a regular deed to be effective, it must: • be in writing, • be signed by the grantor,

20

• identify the grantee, • contain a legal description of the property, and • be delivered to and accepted by the grantee.

For a regular deed, or any deed for that matter, to be recorded, it must be signed before a notary. However, the recording is not a requirement for a regular deed to pass title.

Grantees record the deed to gain protection under the Texas Recording Statute (see Center publication 1267, “Deeds and the Texas Recording Statutes”).

TODDs appear to meet all the formalities except for the delivery to and acceptance by the grantee. However, a review of the statutes reveals that while a delivery may not occur, an acceptance or rejection does.

Take the following example. You are unmarried with a will giving your house to your brother. Subsequently, you execute a TODD giving the same house to your sister. When you die, who gets the house? Basically, which document prevails when the two conflict?

The sister gets that house. Why? Because the TODD removes the house from being a probate asset subject to the terms of the will and changes it to a non-probate one. But can the sister deny (disclaim) acceptance? uppose the house has a fair market value of $50,000.

However, the mortgage and tax liens amount to $100,000.

Does the law require the sister to accept the house?

The answer is no (Section 114.105, Texas Estates Code). The statute allows grantees (designated beneficiaries) the right to disclaim all or a part of the property described in the TODD by complying with Chapter 122 of the Estates Code. This chapter, however, refers to Chapter 240 of the Texas Property Code for a description of the procedure.

According to this chapter, particularly Section 240.009, to be effective, a disclaimer must: • be in writing; • describe and disclaim all or a part of the property described in the TODD;

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• be signed by the person making the disclaimer before a notary so it can be recorded; and • be filed in the deed records in the county where the real property is located. (To assist those who read the document, reference should be made to the volume and page number where the TODD is recorded.)

If the sister files an effective disclaimer, the house would then go to the brother under the terms of the will. So, the TODD gives the grantee/beneficiary the right to passively accept the property or overtly reject (disclaim) it. any married couples believe that community property passes immediately to the surviving spouse when there is no will. This is not true. The surviving spouse may ultimately get the property, but not without administering the estate or filing an affidavit of heirship (see Center publication 2019, “Where There’s No Will . . .”).

TODDs offer a unique opportunity for spouses to deed all or a part of their community real property to the surviving spouse and avoid these procedures. If either spouse changes his or her mind, the deed can be changed or revoked up until the time of death.

Section 114.152 contains a sample TODD to use when the grantor wishes to cancel or revoke the deed. There is no sample form for the grantee wishing to disclaim all or a part of the property.

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Real Estate Licenses and Powers of Attorney Another new statute that generated comments and even a clarification from the Texas Real Estate Commission (TREC) dealt with the limited number of real estate transactions permitted under a power of attorney without the attorney-in-fact having a real estate license. Basically, an attorney-in-fact must have a real estate license when the power of attorney authorizes more than three real estate transactions annually.

This restriction places a barrier on estate planning. Generally, an estate plan encompasses the granting of a durable power of attorney to another to manage one’s affairs in the event of incompetency to avoid a court-appointed guardian.

Requiring the attorney-in-fact to acquire a real estate license may delay the process, increase the costs or limit who can serve.

Effective Jan. 1, 2016, TREC clarified the rule in Section 535.32 of the Texas Administrative Code. The commission changed the requirement from being based on the number of real estate transactions authorized by the power of attorney annually to the number of transactions a real estate agent enters during a calendar year.

Ultimately, though, what the statute and clarification overlook is the fact that the restriction, however worded, does not limit itself to real estate transactions entered under a power of attorney that would otherwise require a real estate license.

There are three places in the law that described real estate transactions. Two of them, the Texas Occupations Code and the Administrative Code, describe transactions in which a real estate license is or is not required.

The third source describes the types of transactions authorized when “real estate transactions” are permitted under a APRIL 2016

power of attorney (see Sections 752.101 and 752.012 of the Texas Estates Code). Real estate transactions are just one of 13 types of transactions that can be authorized under a power of attorney (see Center publication 2044, End of Life Documents).

Many of the real estate transactions described in the Estates Code are specifically exempt from a license under the Occupations Code and the Administrative Code. For example, no license is required for transactions involving the sale, lease, or transfer of minerals. The same activity conducted under a power of attorney may now require a license.

Evidently the drafters overlooked this possibility.

Commingling Funds A distraught employee of a property management company inquired about the manner in which the employer handled security deposits and advanced rental payments.

The company preleases apartments for as long as a year in advance. The rental agreements require tenants to forward the security deposit and two-months rent to hold the lease.

The management company does not deposit the funds in a separate account, but instead uses them to pay commissions and other operational expenses. The attorneys contacted by the employee indicated the practice is standard and legal. Evidently, the practice is widespread.

How do the statutes and administrative code address the practice?

Section 92.106 of the Texas Property Code (which deals with residential property) provides that “The landlord shall keep accurate records of all security deposits.”

The Texas Occupations Code states that the Real Estate Commission may suspend or revoke a license or take other disciplinary actions if the license holder, while engaged in real estate brokerage “commingles money that belongs to another person with the license holder’s own money” (Section 1101.652[b][10]). inally, Section 535.4 of the Texas Administrative Code addresses the matter. It states that a person who controls the acceptance or deposit of rent from a resident of a single-family residential unit must have a license if he or she uses the payment for services related to the management of the property, determines where to deposit the rent, signs checks, or withdraws money from a trust account.

The practice could require certain people to obtain a real estate license or cost brokers and sales agents their licenses.

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Fambrough (judon@tamu.edu) is a member of the State Bar of Texas and a lawyer with the Real Estate Center at Texas A&M University.

THE TAKEAWAY New laws generate opportunities while others restrict them. The Transfer on Death Deed offers opportunities for gifting and estate planning. The limitation on real estate transactions entered under a power of attorney restricts opportunities that otherwise existed.

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Residential

OIL’S IMPACT ON

By Harold D. Hunt

MIDLAND and ODESSA

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HOUSING

ocated in the heart of the Permian Basin, Midland and Odessa are ground zero for the latest downturn in upstream oil and gas (O&G) activity. About one in five jobs in the region are directly related to O&G, the highest percentage in the country.

When indirect jobs dependent on the industry are factored in, it is not surprising that so much attention is being paid to any signs of economic distress in the two cities.

However, this is not their first rodeo when it comes to oil busts, and many locals still remember the lessons learned during the 1980s downturn.

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Correctly predicting future crude prices and their potential impact on the Permian’s O&G industry in the months ahead is impossible. But a look at oil’s effect on Midland’s and Odessa’s employment and housing markets during the last five years does offer an interesting snapshot of the latest boom/bust cycle’s influence on the region through 2015.

Roller Coaster Ride for Crude and Rig Count

most current local monthly employment data from the U.S. Bureau of Labor Statistics (BLS) are produced at the Metropolitan Statistical Area (MSA) level.

The Odessa MSA consists of Ector County only. The Midland MSA added Martin County to Midland County in 2013. While Midland County’s population exceeds 150,000, Martin

Figure 1. Midland and Odessa MSAs Non-Farm Employment vs. Rig Count, WTI Price

Index Value

Although unconventional drilling methods 180 that combine hydraulic fracturing with 160 horizontal drilling have been in use since the 1980s, the real run-up in unconven140 tional drilling began around 2011. Part 120 of the reason for the increase was a strong crude price.

100 The monthly average price of 80 West Texas Intermediate (WTI) Rig Count crude registered above $100 60 Midland MSA Non-Farm Employment a barrel for at least three Odessa MSA Non-Farm Employment 40 months in the four years West Texas Intermediate Price 20 since 2011, according to the federal government’s 0 Energy Information 2011 2012 2013 2014 2015 Administration (EIA).

Sources: Baker Hughes, U.S. Energy Information Administration, and U.S. Bureau of Labor Statistics April 2011 marked the peak average price of $110 while 2014 recorded the Figure 2. most months above $100 Midland County Existing Residential Sales vs. Rig Count at six.

300 Crude price began a fairly rapid descent in 250 October 2014 when Saudi Arabia declined to reduce 200 its production to support it. After a dip into the $40s, crude again rose to plateau 150 briefly at a still low $60 per barrel in June 2015. By year-end 100 2015, prices had declined well into Closed Listings (Sales) Rig Count the $30s.

50 Rig count in the Permian Basin has been extremely sensitive to the price of 0 crude during this cycle. The Permian rig 2011 2012 2013 2014 2015 count began 2011 at about 360 rigs, peakSources: Baker Hughes and Real Estate Center at Texas A&M University ing at a monthly average of 529 during June 2012 based on calculations using County’s population is estimated at less than Baker Hughes weekly data. By December 2015, 6,000. As a result, Midland County domirig count had collapsed to 211, a 60 percent nates the Midland MSA’s statistics. decline.

The Midland and Odessa MSAs began 2011 Rig Count’s Impact on Employment with a total non-farm employment of 73,000 Just as rig count is sensitive to crude price, and 62,900, respectively. By December 2015, Midland’s and Odessa’s employment growth is employment had increased to 91,700 (+26 peralso sensitive to changes in the rig count. The cent) and 74,200 (+18 percent), respectively.

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Permian Basin Counties As defined by the Permian Basin Petroleum Association

PARMER CASTRO SWISHER BRISCOE

BAILEY

LAMB

HALE

FLOYD

HALL

MOTLEY

COCH- HOCKLEY LUBBOCK CROSBY DICKENS RAN YOAKUM TERRY

LYNN

GARZA

KENT

CHILDRESS

COTTLE KING

HARDEMAN FOARD

WILBARGER

KNOX

BAYLOR

STONETHROCKWALL HASKELL MORTON

JONES SHACKLEDAWSON BORDEN SCURRY FISHER GAINES FORD The peak in year-over-year employment growth occurred CALLAMARTIN HOWARD MITCHELL NOLAN TAYLOR ANDREWS HAN almost simultaneously in both STERCOKE EL PASO LOVING WINKLER ECTOR MIDLAND GLASS- LING MSAs, reaching 10.5 percent in RUNNELS COLEMAN COCK BROWN July 2011 in Midland and 11.2 MILLS WARD HUDSPETH TOM CRANE CULBERSON IRION UPTON REAGAN GREEN CONCHO REEVES percent in August 2011 in Odessa.

MCCULLOCH SAN SABA The peaks occurred just months MENARD PECOS SCHLEICHER JEFF DAVIS CROCKETT MASON LLANO after the April 2011 crude price KIMBLE SUTTON peak.

TERRELL The growth rate began to drop PRESIDIO VAL VERDE KERR EDWARDS KENDALL BREWSTER noticeably by first quarter 2015 REAL BANDERA in both MSAs. Total non-farm employment growth from DecemKINNEY MEDINA UVALDE ber 2014 to December 2015 registered a negative 7.1 percent for the 2014 was double its January 2011 level, the Midland MSA while Odessa MSA employment index value for that month would be 200. growth declined by 9.2 percent. rude price, although fairly volatile, continued an upward trend through midIndex Use for Comparisons 2014 (Figure 1). During the same period, An index has been used to evenly compare the the Permian Basin rig count was growing at an magnitude of changes in variables being diseven faster rate. These increases are reflected in cussed, using January 2011 as the starting point the positive impact on non-farm employment or “base.” The base value is 100, and the index growth observed in both Midland and Odessa. numbers over time are expressed as a ratio to While the downward momentum in crude the base value. For example, if rig count in June prices had begun by mid-2014, rig count held on another five months before it began its slowdown in December. Non-farm employment growth in both MSAs began its decline a month later in January 2015.

Unfortunately, the BLS also combines O&G employment with construction employment in the Midland and Odessa MSA statistics. This limitation makes a pure look at O&G Midland County Existing Residential Prices employment impossible. However, and Inventory vs. Rig Count mining and logging and construction employment growth in percentage terms far exceeded growth in total non-farm income in both MSAs. In the Midland MSA, an increase of 7,200 mining and logging and construction jobs was recorded between January 2011 and December 2015, a 41 percent increase.

In the Odessa MSA, the increase was Rig Count lower—3,500 additional jobs for a 27 perMedian Close Price cent increase during the same period.

Average Close Price PSF

C

Figure 3.

180 160

Index Value

140 120 100 80 60 40 20

Months Inventory

0 2011

2012

2013

2014

Sources: Baker Hughes and Real Estate Center at Texas A&M University

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2015

Housing Market Observations Expanded Real Estate Center data capabilities allow the new and existing housing markets to be examined independently. However, “new” homes are only new construction that has been listed in the local multiple listing service (MLS) systems, and this represents only a limited percentage of new

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Midland County Existing Home Sales

Index Value

home sales. Other new homes sold in-house by the sales staff of individual builders is not part of the new home analysis.

The bulk of home sales in Midland and Odessa occurs in two counties, Ector County for Odessa and Midland County for Midland. As a result, those two coun300 ties are used exclusively for comparison in the following discussion.

The analysis uses monthly data to cover 250 the five-year period between January 2011 and December 2015. Housing statistics 200 also include condos and townhomes.

Figure 4.

Ector County Existing Residential Sales vs. Rig Count

150

2015

2016

Prices

Index Value

100 A significant drop in existing sales Closed Listings (Sales) occurred in the second half of Rig Count 2014 as rig count declined (Figure 50 2). Monthly sales bottomed at 78 in February 2015, the lowest 0 monthly total observed during 2011 2012 2013 2014 the five-year analysis.

Sources: Baker Hughes and Real Estate Center at Texas A&M University A surprisingly strong rebound in sales occurred by mid-2015.

July 2015 registered 210 existing Figure 5. Ector County Existing Residential sales, the highest monthly total and Inventory vs. Rig Count 200 over the analysis period. Sales Median Close Price also ended 2015 on a strong posi180 Average Close Price PSF Rig Count tive trend.

160 Months Inventory A sharp increase in months inven140 tory coincided with the drop in rig count beginning in late 2014 (Figure 3).

120 The move up began in September 2014 100 from an extremely low 2.2 months inven80 tory, increasing to a mere 4.0 months by 60 year-end 2015. About 6.5 months inventory is considered to be a balanced market 40 with no advantage to sellers or buyers.

20 The continued tightness in inventory 0 is also reflected in the lack of any per2011 2012 2013 2014 ceptible drop in median closing price or Sources: Baker Hughes and Real Estate Center at Texas A&M University average closing price per square foot by year-end 2015.

Sales price distribution reveals a signifiEctor County Existing Home Sales cant upward migration in existing home sale xisting home sales in Ector County also prices also occurred between 2011 and 2015. dropped as rig count plunged in late 2014 The percentage of home sales up to $199K (Figure 4). However, the decline was not declined while sales between $200K and $999K as deep as in Midland. While 2015 sales actually increased. bottomed at 59 in February, sales in the same Improving incomes related to a more vibrant month in 2014 had been even lower at 56.

O&G sector probably contributed heavily to The peak in monthly sales over the analysis this upward trend. About 73 percent of existing period occurred in July 2014 at 113, but July homes sold in 2015 were priced between $150K 2015 was only two sales short of that at 111. and $399K.

2015

2016

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A

lthough Ector County’s increase in months inventory occurred later than Midland’s, the rate of increase was much steeper (Figure 5). Ector County ended 2015 with a moderately higher 5.0 months inventory.

Again, owing to the low inventory level, median closing prices and average closing price per square foot remained solid through year-end 2015.

Figure 6. Midland County New Residential Sales and Permits vs. Rig Count

900 800

SF Building Permits Closed Listings (Sales) Rig Count

Index Value

700 600 500 400 300 200 100 0 2011

2012

2013

2014

2015

Sources: Baker Hughes and Real Estate Center at Texas A&M University

Figure 7. Midland County New Residential Prices and Inventory vs. Rig Count

180 160

Index Value

140 120 100 80 60 40 20 0 2011

Rig Count Median Close Price Average Close Price PSF Months Inventory

2012

2013

2014

Sources: Baker Hughes and Real Estate Center at Texas A&M University

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2015

Similar to Midland, Ector County also experienced an upward price migration during the five-year period. A lower percentage of sales occurred between 2011 and 2015 in the bottom price range through $149K. Meanwhile, the percentage of sales increased between $150K and $399K. The sweet spot of existing sales in 2015 occurred between $100K and $249K, where 71 percent of all sales occurred. This range is noticeably lower than where the bulk of sales occurred in Midland that same year.

Midland County New Home Sales

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ingle-family building permits are included in Figure 6 along with new home sales. Strong spikes in issued permits occurred in July 2014 and June 2015. Peaks in new home sales also occurred at nearly the same time.

A fairly significant dip in sales occurred in January 2015 as rig count began to decline.

However, the sales trend quickly turned up again, ending 2015 in a positive direction. Peak monthly sales for the five-year 2016 period topped out at 39 in July 2015.

Months inventory continued to tighten through August 2014 as rig activity increased, bottoming at an extremely low 1.1 months (Figure 7). As rig count went into decline, months inventory again began to move up.

The increase through April 2015 only lifted it slightly to 2.8 months, at which point it again began to fall. As of year-end 2015, no new homes were listed for sale through the local MLS system.

Based on available data, builders 2016 appear to have been proactive in shutting down the new inventory pipeline quickly as the O&G sector worsened.

This conclusion is supported by the lack of any meaningful downturn in median closing prices and average closing price per square foot through year-end 2015.

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The bulk of new home sales in 2015, about 64 percent, occurred in properties priced between $150K and $249K.

Ector County New Home Sales

Index Value

Figure 8. Ector County New Residential Sales Similar to Midland, Ector County had and Permits vs. Rig Count two significant spikes in new home 900 permits (Figure 8). However, the spikes occurred much earlier, with the larg800 SF Building Permits est registered in June 2013 followed 700 Closed Listings (Sales) by another three months later in Rig Count 600 September.

New home sales dipped 500 briefly two times, once in 400 January 2014 and again in January 2015. The sec300 ond drop coincided with 200 the falloff in rig count.

However, both dips were 100 followed by lengthy pos0 itive sales trends, with 2011 2012 2013 2014 2015 year-end 2015 ending Sources: Baker Hughes and Real Estate Center at Texas A&M University on a solid upward note.

Months inventory has been quite volaFigure 9. Ector County New Residential Prices tile during the analyand Inventory vs. Rig Count 200 sis period (Figure 9).

Rig Count However, the peak in 180 Median Close Price Average Close Price PSF months inventory that 160 Months Inventory occurred in October 2012 140 only brought the level to an 120 extremely tight 2.6 months. ithout data on 100 in-house sales by 80 homebuilders, it is 60 difficult to say whether such a low inventory level is truly repre40 sentative of the market. However, the 20 strength in median closed prices and 0 average closed prices per square foot 2011 2012 2013 2014 2015 lends support to an extremely tight new Sources: Baker Hughes and Real Estate Center at Texas A&M University home market.

Just as in Midland County, builders appear to have been quite vigilant with no new homes listed for sale through the local MLS THE TAKEAWAY system by year-end 2015.

Sales prices migrated up between 2011 and No one knows whether more bad news lies 2015, primarily from the $100K to $199K range ahead for the Permian Basin’s O&G sector to the $200K to $249K bracket. About 64 perin the coming years. Oil can be an unprecent of new home sales in 2015 were between dictable commodity. But the data appear to $150K and $249K, with the real sweet spot show that Midland’s and Odessa’s housing occurring between $200K and $249K. markets weathered the oil and gas downturn amazingly well through 2015, even as Dr. Hunt (hhunt@tamu.edu) is a research economist with employment declined. the Real Estate Center at Texas A&M University.

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Index Value

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2016

2016

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Taxes

Less Tax?

By Jerrold J. Stern

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ome tax advisors refer to client situations as having either “good facts” or “bad facts.” As you might suspect, good facts typically lead to favorable tax results while the opposite is true for bad facts. In real estate scenarios, good facts pertain to adequate documentation of business activities as well as the activities themselves.

The tax cases described here provide examples of how real estate holdings led to favorable tax treatment because of the taxpayers’ good facts. Good tax planning aided by expert tax advice can lead to good tax facts.

The first example of good facts concerns in a recent tax court case involving the Fitches. Mr. Fitch is a CPA and Mrs. Fitch is a Realtor. They owned eight rental properties in California. The Fitches maintained careful records documenting their day-to-day management of the properties. They personally performed almost all of the following: bookkeeping, repairs, contractual arrangements, tenant screening, advertising, paying taxes and utilities, acquiring insurance, and working with homeowner associations. There were tax losses on all of the properties for the tax years in question. The Fitches chose to go to tax court because the IRS disallowed virtually all of their rental property deductions.

Mr. Fitch and his brother co-owned one of the properties and tried to sell it immediately after it was inherited from their mother. However, they were not able to attract a satisfactory offer. Mr. Fitch decided to purchase his brother’s one-third interest in the property so it could be rented. The purchase was a key factor in the eyes of the court.

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But in addition, the Fitches used a “for rent” sign, advertised on Craigslist, and obtained insurance for landlord protection. “Credible testimony” was given in court regarding weekly property management. The tax court ruled against the IRS and allowed all related expenses to be deductible even though the property was never actually rented.

For another property, Mrs. Fitch testified that she and her husband were the key people involved in advertising, decorating, working with contractors, selecting tenants, and handling the keys and lockbox. The IRS argued that the Fitches’ testimony should be disregarded on the grounds that it was self-serving, but the court found their testimony to be “credible and persuasive,” resulting in a loss for the IRS and a win for the Fitches. nother example of a taxpayer victory occurred in a case involving Hattie Bonds. Ms. Bonds converted her Kansas City home from a personal residence to a rental property when she moved to Minnesota. The property was rented to a variety of tenants. However, during one year in particular, Ms. Bonds was unable to rent the property.

The court was impressed by the fact that Ms. Bonds continued to try to rent the property even though it had appreciated in value.

While Ms. Bonds did not have complete documentation of her expenses, the court viewed the other evidence as sufficient, such as mortgage documents and some bills. Thus, the court was willing to estimate her deductions by applying the “Cohan rule.” This rule was established in 1930 in a case involving George M. Cohan, a famous actor, playwright

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and musical artist. In Mr. Cohan’s case, the court was willing to estimate deductible entertainment and travel expenses based on documentation showing that he made many trips and held parties attended by other celebrities. n general, the IRS would rather settle or compromise with a taxpayer than go to court and lose. All court cases become public information, and the IRS does not normally want to give taxpayers “ammunition” to use to game the system to save taxes. Over 90 percent of disputes with the IRS are settled out of court, according to taxattorneydaily. com and investopedia.com. Thus, it is not surprising that the large majority of cases that end up in tax court result in IRS victories. For those going to court, taxpayers have only won part or all of their cases approximately 14 percent of the time, according to the IRS Taxpayer Advocate’s office.

Good facts resulting in taxpayer victories don’t always occur on their own.

Astute tax planning can help. Such tax planning can be obtained with the help of a tax accountant or attorney knowledgeable in real estate matters.

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Dr. Stern (stern@indiana.edu) is a research fellow with the Real Estate Center at Texas A&M University and a professor of accounting in the Kelley School of Business at Indiana University.

THE TAKEAWAY Good tax planning aided by expert tax advice can lead to “good facts.”

Good facts, which can lead to tax savings, are taxpayer circumstances and actions respected by the tax court and the IRS. TIERRA GRANDE

IT’S OUR ANNIVERSARY

Helping Texans make better real estate decisions since 1971.

Learn more about our history at https://www.recenter.tamu.edu/about-us/our-history/ APRIL 2016

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