DETERMINANTS OF THE CAPITAL STRUCTURE OF RESIDENTIAL PROPERTY COMPANIES Björn-Martin Kurzrock...

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DETERMINANTS OF THE CAPITAL STRUCTURE OF RESIDENTIAL PROPERTY COMPANIES Björn-Martin Kurzrock Frieder Mokinski Felix Schindler Peter Westerheide

Transcript of DETERMINANTS OF THE CAPITAL STRUCTURE OF RESIDENTIAL PROPERTY COMPANIES Björn-Martin Kurzrock...

Page 1: DETERMINANTS OF THE CAPITAL STRUCTURE OF RESIDENTIAL PROPERTY COMPANIES Björn-Martin Kurzrock Frieder Mokinski Felix Schindler Peter Westerheide.

DETERMINANTS OF THE CAPITAL STRUCTURE OF RESIDENTIAL PROPERTY COMPANIES

Björn-Martin Kurzrock

Frieder Mokinski

Felix Schindler

Peter Westerheide

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Motivation of the Research

• Concept of financial leverage is a paradigm in real estate investment

• Debt offers a variety of benefits and downsides that affect financial performance in multiple ways

• Do German Residential Property Companies (RPCs) systematically adjust their capital structure?

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Aim of the Research

• Identify considerations that drive the capital structure choice of German RPCs

• Identify differences among the major legal forms (eG, GmbH, GmbH & Co. KG, AG)

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Potential Considerations I: Overview

• Pecking Order Theory: Firms prefer internal to external funding ↔ asymmetric information costs

• Trade Off Theory: Firms choose capital structure as a compromise between costs and benefits of debt and equity funding

• Market Timing Theory:Firms adjust capital structure to market prices of

debt and equity

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Potential Considerations II: POT

Pecking Order Theory (Myers/Majluf 1984) I:

• Management: superior information, acts in owners’ interest

• Outside investors: inferior information; reasoning: management raises equity capital if & only if company is overvalued by market

Asymmetric information ↔ raising equity capital harms owners

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Potential Considerations III: POT

Pecking Order Theory (Myers/Majluf 1984) II:

Debt: lower exposure to information asymmetry ↔ fixed payment…

Hierarchy of financing sources: 1. retained profits, 2. debt, 3. equity

Empirical implication: Unless leverage is extreme, financing deficits are covered through debt:

“Change in Debt” = “Financing Deficit”

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Potential Considerations IV: TOT

Trade Off Theory (inter alia Kraus/Litzenberger 1973) I:

• Capital structure choice balances benefits and costs of financing sources/additional leverage

• Benefits of Debt: tax shield, mitigation of agency conflicts between owner and manager, monitoring/control etc.

• Costs of Debt:growing bankruptcy risk, rising costs of financial distress, agency conflicts between manager and bank (e.g. incentive for asset substitution) etc.

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Potential Considerations V: TOT

From: Shyam-Sunder/ Myers (1999), p. 220.

Target Debt Ratio

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Potential Considerations VI: TOT

Trade Off Theory (inter alia Kraus/Litzenberger 1973) II:

Empirical Implication: Firms adjust their leverage towards a target debt ratio:

“Change in Debt” = “a” x (“Actual Debt”–“Target Debt”)

• “a” є [-1,0] – share of the deviation of actual debt from target debt that is closed during a period

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Potential Considerations VII: MTT

Market Timing Theory (Baker/Wurgler 2002):

• Firms: issue equity when equity prices are high and costs of equity are low compared to interest on debt

Potentially long lasting effects on the capital structure

Influence of structural characteristics of the firm can be blurred

• Not tested here

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Data I: Overview

• Panel of German RPCs (Dafne Database/ Bureau van Dijk)

• Sample period: 1996 – 2009

• (Unsystematic) missing values reduce regression samples

• >1,300 companies

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Data II: Summary Statistics

• Leverage Ratios, Financing Deficits, Target Debt Ratio:

.1771938 .1615736 .1624042 Total .6162779 -.0398518 .6298736 .1703525 .0337515 .1634075 eG .5723705 -.0263179 .5853424 .3192767 .8892446 .3166905GmbH & Co. KG .7291707 -.2941441 .7502914 .171389 .1508262 .1481759 GmbH .6411379 -.0441297 .6525574 .1313661 .0558745 .0915592 AG .6947949 -.0189269 .7414091 legal_form leverage deficit target~e

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Empirical Strategy I: POT

• Tests according to Shyam-Sunder/ Myers (1999) (and others)

• Stylized POT test regression: ΔDit = a + bPOTDEFit + eit

whereΔDit = Net change in debt of firm i in period t, andDEFit = Financing deficit of firm i in period t, anda & btot are coefficients, andeit = random disturbance.

• Modification: DEFit interacted with legal form dummies

• Prediction of the POT: a = 0, bPOT = 1

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Empirical Strategy II: POT

Construction of involved variables:

• ΔDit = Dit – Dit-1whereDit = overall Debt of firm i in period t

• Financing deficit:DEFit = DIVit + Xit+ ΔWit – Cit where

DIV = dividend payments

X = capital expenditure ( = change in tangible assets)

ΔW = net increase in working capital

C = operating cash flow after interest and taxes

Note: No equity issues/ repurchases in DEF! Equity issues at high debt levels will improve the fit of TOT model and degrade the fit of this POT model (Shyam-Sunder/ Myers (1999), p. 225)

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Empirical Strategy III: TOT

• Stylized TOT test regression:ΔDit = a + bTOT(Dit-1 - D*it-1) + eit

where D*it = target debt level

• Modification: DEFit interacted with legal form dummies

• Prediction of the TOT: bTOT є [-1,0] (implying adjustment towards target ratio and positive adjustment costs)

• Construction of D*: [simple/ moving] average of firm leverage over preceding years (cf. Shyam-Sunder/ Myers 1999)

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Empirical Results: POT

* p<0.05, ** p<0.01, *** p<0.001t statistics in parentheses R-sq 0.311 0.348 0.304 0.191 N 4391 4026 1354 476 (5.73) (5.95) (3.52) (-3.50) _cons 0.00794*** 0.00896*** 0.00833*** -0.0250***

(-0.46) def_gmbhcokg -0.102

(2.57) def_eg 0.407*

(-0.87) def_ag -0.0808

(3.30) def 0.244***

(-3.05) (-1.36) (-0.99) def2_gmbhc~g -0.215** -0.183 -0.124

(8.41) (8.20) (9.53) def2_eg 0.411*** 0.412*** 0.547***

(0.25) (0.16) (5.86) def2_ag 0.0525 0.0343 0.604***

(3.61) (3.77) (1.91) def_2 0.216*** 0.237*** 0.144 pot s1 pot big pot s3 pot ssm (1) (2) (3) (4)

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Empirical Results: POT

• POT:

- Coefficients fairly stable across specifications

- GmbH (base cat.): cover 23% of DEF through debt

- eG coefficent closest to 1 (0.63)

- AG and GmbH & Co. KG coefficient not significantly different from 0

POT prediction fails for AGs – i.e. where we would

expect it to hold ≠ Shyam-Sunder/ Myers (1999)

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Empirical Results: TOT

* p<0.05, ** p<0.01, *** p<0.001t statistics in parentheses R-sq 0.022 0.022 0.024 N 1735 1319 1354 (-3.14) (-2.99) (-2.05) _cons -0.00373** -0.00314** -0.00242*

(-0.93) (1.57) (1.43) d_dev_GMBH~G -0.122 0.266 0.282

(-2.97) (-0.60) (-1.93) d_dev_EG -0.136** -0.0404 -0.0943

(0.41) (0.51) (0.42) d_dev_AG 0.0805 0.122 0.101

(-2.12) (-2.52) (-2.52) d_deviation -0.0547* -0.0988* -0.0815* tot s2 tot big tot s3 (1) (2) (3)

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Empirical Results: TOT

• TOT:

- Again: fairly stable across specifications

- Coefficient significantly different from zero only for GmbHs and eGs; however, small coefficients, low R²

Minor adjustment towards a target ratio

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Empirical Results: Interpretation

• Except for GmbHs and eGs: No indication of systematic adjustments to capital structure! – WHY?:

Firms exploit cheapest sources of funding available when they need to cover a financing deficit? (Market timing theory?)

Failure to maximize company value?

Considerations such as information asymmetries fail for RPCs: rare growth opportunities, largest part of firm assets are tangible?

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Limitations & Further Research

• Simple models to test POT and TOT

• No test of MTT (yet)

• Impact of financial leverage on the performance of property companies (requires long-term analysis)

• Relationship with stock performance for publicly-traded companies

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Contact

Dr. Björn-Martin Kurzrock*

Frieder Mokinski**

Dr. Felix Schindler**

Dr. Peter Westerheide**

* University of Kaiserslautern

Dept. A/ RU /BI

Paul-Ehrlich-Straße 14, D-67663 [email protected]

** Center for European Economic Research

Dept. Int. Finance and Financial Management

P.O.-Box 10 34 43 D-68034 [email protected]; [email protected]; [email protected]