The Relationship Between Firm Investment and Financial Status

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Transcript of The Relationship Between Firm Investment and Financial Status

COURSE TITLE: SEMINOR IN FINANCE COURSE CODE: MPH 622

Presentation on

The relationship between firm investment and financial status

Written by: Sean Cleary, Saint Mary’s University, Halifax

Published in: Journal of Finance, Vol. LIV, No. 2, April 1999

30th March, 2011

Article OutlineI. Background

A. Evidence of financing hierarchy

B. Conflicting views

C. Motivation

II. Research designA. Sample characteristics

B. Classification methodology

C. Regression estimation

D. Determination of significance level

III. Discussion of resultsA. Results

B. Interpretation

IV. Conclusions

Presentation Outline

Background

Motivation of the study

Research Methodology

Major Findings

Conclusions

Comments

Investment decisions and financial factors are related issues.

The controversy found in the literature on the ground that the relationship is changing.

Modigliani and Miller (1958) - Financial factors are irrelevant for investment decisions.

Greenwald, Stiglitz, and Weiss (1984), Myers and Majluf (1984), and Myers (1984) Bernanke and Gertler (1989, 1990) and Gertler (1992) - Financial structure may be relevant to the investment decisions.

Background

Fazzari, Hubbard, and Petersen (1988), Hoshi, Kashyap, and Scharfstein(1991), Oliner and Rudebusch (1992), Whited(1992), Schaller (1993), and Gilchrest and Himmelberg (1995) also are in favor for the relevance of financial status.

The investment decisions in market imperfection are sensitive to the availability of internal funds .

Reason: low cost over external funds.

Back…..

Fazzari, Hubbard, and Petersen (1988) - Use Value Line data, 422 U.S. mfg. firms, 1970 to 1984, and found that internal funds have cost advantage.

Hoshi et al. (1991) – Studied on 146 Japanese mfg. firms and revealed that the investment outlays are much more sensitive to firm liquidity.

Oliner and Rudebusch (1992) - Examine 120 U.S. firms, 1977 to 1983 period and found that investment is most closely related to cash flow.

Back…..

Schaller (1993) - Studied 212 Canadian firms, 1973 to 1986, and concluded that firm investment with dispersed ownership concentration is the most sensitive to cash flow.

Whited (1992) & Bond and Meghir (1994) - Use an Euler equation approach, 325 U.S. mfg. firms, 1972 to 1986 period & 626 U.K. mfg. firms from 1974 to 1986 period found exogenous finance constraint to be particularly binding for the constrained groups of the firms.

Mayer (1990) - Examined the sources of industry finance of eight developed countries from 1970 to 1985 and found that:i) Retentions are the dominant source of financing in all

countriesii)The average firm in any of these countries does not raise

substantial amounts of financing from security markets. and,

iii) The majority of external financing comes from bank loans in all countries.

Objective of the study

A major focus of this study is the comparison of investment-liquidity sensitivities across different groups of firms.

Back…..

Research Gap

The contrariety conclusion of Kaplan and Zingales’s study.

Implications of the results.

Limitations of Kapland and Zingles’s study: Sample (49 manufacturing firms)

Value line database

Too small sub-groups (22, 19 and 8)

Sorting criteria

Subjective and possibility of self-serving managerial statements, etc.

Motivation

Approach applied = Kaplan and Zingales Approach(NFC = increase cash div., NC = large cash position., Unconstrained = financially healthy firm with low debt & high cash)

Statistical toolsMultiple discriminant analysis (similar to Altman’s Z factor)Bootstrap methodology (Sign. level)Correlation matrixRegression analysisDescriptive statisticsFinancial constraint index, etc.

Sample size = 1317 firmsStudy period = 1987 to 1994

Methodology

Sample composition

Listed company view Firms SIC code view Firms

NYSE 709 Mfg. firms (SIC codes 2000–3999) 843

Nasdaq 416 Agri., mining, forestry, & Cons. (SIC codes 1–1999) 99

AMEX or US exchange 192 Retail and wholesale trade (SIC codes 5000–5999) 201

Service firms (SIC codes 7000–8999) 174

Sample size 1317 Sample size 1317

Method…

Basic conditions for samples selection:

a) Banks, insurance companies, other financial companies, and utility companies is avoided, and

b) Required to have positive values for sales, total assets, net fixed assets, and market-to-book ratio.

i) Standardized discriminant function (ZFC )

ZFC = b1Current + b2FCCov + b3SLACK/K 1 b4 NI% + b5 Sales Growth + b6 Debt.

Z score help to classify the entire sample in to 3 groups (Group I – Increase DPS, II – Decrease DPS and III – No change in DPS)

ii) regression model is also used.

I/Kit = bM/B(M/B)it + bCF/K(CF/K)it + uit

iii) A bootstrapping procedure is used to calculate empirical p-values

Method…

TotalSample

Group 1Increase DPS

Group 2Decrease DPS

Group 3No change in DPS

Net fixed assets $650m $1076m $913m $630

Current ratio 2.57 2.40 2.36 2.71

Debt ratio 0.22 0.20 0.26 0.23

Fixed charge coverage 12.1 16.8 7.4 9.9

Net income margin(%) 3.0 6.8 1.0 1.0

Market to Book ratio 2.18 2.64 1.62 1.97

Sales growth(%) 10.1 11.4 1.6 10.3

Slack/K 1.71 1.42 1.45 1.92

Cash flow/K 0.47 0.58 0.27 0.42

Investment/K 0.26 0.26 0.19 0.24

Discriminant score (Z) -0.31 0.17 -0.87 -0.61

Table I - Sample Summary Statistics (1988-1994)

Panel A: Selected Financial Ratio Means

Finding: Firms with reducing dividends appear to be more financially constrained. (Low where as high is desire)

Dividend Group Total Sample

1988 1989 1990 1991 1992 1993 1994

1. increased DPS 324135.1%

54741.5%

54341.2%

47836.4%

40831.0%

41131.2%

42031.9%

43433.0%

2. increased DPS 6366.9%

584.0%

685.2%

947.2%

1279.6%

1108.4%

916.9%

916.9%

3. no change in DPS 534458.0%

71754.5%

70653.6%

74556.6%

78259.4%

79660.4%

80661.2%

79260.1%

Panel B: Number of Firms per Dividend Group

Finding: Largest number of firms 547 occurred in 1988 in

first group and 127 firms in second group for the

year 1991.

This evidence supports the notion that firms face

changing levels of financial constraints every

year.

CF/FA CR DR FCC INV/FA M – B R NIM SG Slack/FA D Score

CF/FA 1

CR .11 1

DR -.18 -.33 1

FCC .21 .19 -.43 1

I/FA .37 .17 -.23 .18 1

M to BR .21 .02 -.12 .21 .24 1

NIM .34 .08 -.14 .24 .13 .10 1

SG .19 .02 -.01 .11 .24 .20 .21 1

Slack/FA .38 .47 -.33 .13 .40 .08 .02 .05 1

D Score .32 -.07 -.29 .32 .18 .19 .80 .55 -.08 1

Table II - Correlation among variables

Measure liquidity ratio but it is surprising (-ve)

High correlation between D. Score and NIM followed by SG

Finding: 26% of the cases are misclassified in predicting

whether firms will cut or increase their dividend.

Table III - Selected Financial Ratio Means forFinancially constrained Groups(1988-1994)

Predicted Group 1

Predicted Group 2

FC Firms PFC Firms

NFC Firms

Net fixed assets $803m $591m $507m $787m $656m

Current ratio 2.37 2.51 2.74 2.37 2.62

Debt ratio .18 .28 .31 .22 .14

Fixed charged coverage 18.3 4.8 3.0 8.8 24.6

Net income margin(%) 7.2 -1.2 -4.8 4.2 9.6

Market to Book ratio 2.58 1.50 1.65 1.91 2.99

Sales growth(%) 15.1 -.6 -2.3 9.0 23.5

Slack/K 1.30 1.30 1.93 1.46 1.75

Cash flow/K .52 .24 .23 .42 .75

Investment/K .27 .19 .21 .24 .33

Discriminant score(Z) .51 -1.45 -1.77 -.21 1.05

Findings: Financial ratios are superior for the NFC group,

inferior for the FC group and the PFC in between.

The observed average turnover rates are 40.9, 52.3, and 37.3 percent per year.

Firms are classified at least one year is 75, 83 and 74 percent for the NFC, PFC, and FC respectively.

Only 17 firms are classified as PFC for all 7 years, and only 49 and 80 are classified as NFC and FC.

These results indicates that individual firm’s financial status does change significantly y-b-y.

Table IV – Regression results for the total

sample (1317 firms)

Findings

Firm’s investment decisions are sensitive to market opportunity (M-B) but are even more sensitive to liquidity variable (CF/NTA)

Liquidity and market to book ratio are significant determinants of investment for FC, PFC and NFC groups

Investment outlays of the NFC firms are significantly more sensitive to liquidity than that of PFC and FC firms. Estimated coefficients are 0.153, 0.090 & 0.064 with p value 0.0046, 0.000 & 0.083 respectively.

p value 0.5890 explains NFC>FC at 058.90% level of sign.

Table V – Regression results for dividend

payout groups

Investments of the NFC firms are most sensitive to liquidity followed by PFC firms and FC firms. Coefficients are 0.159, 0.080 & 0.057 with p values 0.002, 0.000 & 0.1378 respectively.

p value 0.3834 explain NFC>FC at 38.34 level of significance.

Similar explains for the next panels as well.

The study concludes the accuracy of the classification is 74 percent in predicting dividend payments.

The investment decisions of firms with high creditworthiness (least financially constrained) are significantly more sensitive to the availability of internal funds than are firms that are less creditworthy.

This strongly supports the small-sample evidence of Kaplan and Zingales (1997).

Conclusions

A strong effort to validate the conclusions of earlier study using varying research methodology.

Sound methodology of the study.

Statistical tools and models used for the analysis are clearly described.

The motivation of the study presented with the evidences of the literatures in a details.

Determination of significance level has done which is rare in existing literature.

Comments

Thank you.