## 8. Response of Firms to Monetary Contraction: Summary Features

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---

### I. Introduction and purpose
- Objective: Investigate the association between corporate finance and monetary policy in India over the period 1992 to 2003 using firm-level data, distinguishing firms by ownership and governance, and across sub-periods.
- Conceptual context:
  - Modigliani-Miller (financing choice irrelevant in perfect markets) and pecking-order (internal finance preferred; debt over equity).
  - Two monetary transmission views: credit view (bank-dependent firms more affected by monetary tightening) and relationship lending (long-term bank–firm relationships mitigate cyclical loan supply changes).
- Sample: manufacturing firms maintaining identity and reporting annual accounts without gaps for 1992 through 2003; final sample size: 525 firms.

### II. Data and institutional background
- Data source and coverage:
  - Prowess database (Release 2.1) maintained by CMIE; database contains financial information on over 8,000 companies, including listed and major unlisted public limited companies having sales in excess of Rs.10 million.
  - Unlisted entities qualify if average sum of sales and total assets ≥ Rs.200 million (latest audited results).
  - USD 1≈Rs.45.
  - Private company minimum paid-up capital Rs.0.1 million; public company minimum paid-up capital Rs.0.5 million.
  - Listing thresholds: minimum paid-up equity capital not less than Rs.100 million; post-issue capitalization not lower than Rs.200 million; for listed companies considered, minimum market capitalization should be Rs.500 million and post-issue net worth should be Rs.200 million.
- Sample composition highlights:
  - Around 33 percent of firms are in chemicals, machinery and textile sectors.
  - About 5 per cent of companies in the sample are public; they account for nearly 27 per cent of total assets of firms.
  - Over 80 percent of private firms in the sample are listed.
- Financial sector reform chronology:
  - Pre-1992: strong constraints on equity access (Controller of Capital Issues) and long-term debt largely via development banks.
  - 1991–1997 reforms included heavy statutory preemptions (example: commercial banks had to hold as much as 63.5 per cent of increases in deposits in cash reserves and government debt instruments; 40 percent of credit to designated priority sectors).
  - 1992: CCI abolished; freer access to capital markets under SEBI oversight.
  - 1997: Bank Rate activated as signaling rate; statutory pre-emption on bank deposits gradually lowered; since April 1, 1997, automatic monetization replaced by Ways and Means Advances (WMA).

### III. Empirical strategy and variables
- Estimation framework:
  - Panel regression with fixed effects, time dummies included.
  - Primary reduced-form specification: Yit = α*Xit + β1*MPIt + β2*MPIt-1 + γ*MPIt*LISTEDt + eit.
  - Controls: INT, TAN, SIZE (log total assets), AGE (years since incorporation), DEPCN, EARN, RND, DIVI; interactions with PRIVATE and LISTED dummies; industry dummies.
- Dependent variables (debt ratios):
  - DEBT = total borrowing to total assets.
  - BKDEBT = bank borrowing to total borrowing.
  - STBANK = short-term bank borrowing to total bank borrowing.
- Monetary policy indicator (MPI): natural logarithm of the yield on 364-day treasury bills (primary market cut-off yield used).

### IV. Key empirical findings
- Correlations and control-variable effects:
  - DEBT and its components are positively correlated with each other and negatively correlated with most control variables.
  - MPI is negatively correlated with debt components (firms tend to reduce debt following monetary tightening).
  - Control-variable signs (intuition preserved):
    - INT: positive with DEBT; linked to lower STBANK.
    - TAN: positive with debt (collateral effect).
    - SIZE: positive with overall debt; negative with STBANK.
    - DEPCN: negative coefficient.
    - AGE: positive with debt.
    - EARN: negative coefficient.
    - DIVI: negative coefficient.
    - RND: negative coefficient.
- Monetary policy effects (whole sample; fixed-effects results):
  - MPI_t: -3.392 (0.06) for DEBT; -2.744 (0.02) for BANK; -1.892 (0.10) for STBANK.
  - MPI_t-1: 1.153 (0.01) for DEBT; 1.042 (0.09) for BANK; 0.473 (0.50) for STBANK.
  - Interpretation: contemporaneous monetary tightening reduces total debt and bank debt; lagged effect tends to increase debt (re-leveraging/renegotiation).
- Ownership and listing differentials:
  - MPI_t * PRIVATE_t: -0.671 (0.58) for DEBT; -1.284 (0.09) for BANK; 0.520 (0.19) for STBANK — private firms proactively lower bank debt relative to public counterparts, overall response muted.
  - MPI_t * LISTED_t: 1.564 (0.07) for DEBT; 1.048 (0.49) for BANK; 1.873 (0.09) for STBANK — listed firms increase overall debt by increasing short-term bank borrowing after tightening (consistent with relationship lending or anticipation of rate changes).

### V. Heterogeneity across periods, size, and leverage
- Sub-periods (1992-97 vs 1998-03) — select MPI coefficients (p-Values in brackets):
  - 1992-97:
    - DEBT MPI_t: -1.135 (0.87); DEBT MPI_t-1: -1.796 (0.00).
    - BKDEBT MPI_t: 1.618 (0.17); BKDEBT MPI_t-1: 1.161 (0.00).
    - STBANK MPI_t: 1.563 (0.31); STBANK MPI_t-1: -1.503 (0.09).
    - Summary: limited contemporaneous effect; stronger lagged effects; corporate responses muted and similar across ownership/governance.
  - 1998-2003:
    - DEBT MPI_t: -1.355 (0.10); DEBT MPI_t-1: 1.973 (0.00).
    - BKDEBT MPI_t: -2.955 (0.07); BKDEBT MPI_t-1: 1.001 (0.05).
    - STBANK MPI_t: 1.366 (0.10); STBANK MPI_t-1: 1.739 (0.21).
    - Summary: contemporaneous and lagged impacts—immediate lowering of debt and subsequent re-leveraging; private firms actively lowered bank debt; listed firms increased bank borrowing to maintain relationships.
- Size-based sub-samples (top 20% vs bottom 20%):
  - Small firms (bottom 20 percentile, Number of Firms: 105):
    - MPI_t for DEBT: 0.660 (0.10); for BANK: 0.319 (0.06); for STBANK: -0.378 (0.10).
    - Evidence: small firms often increase bank debt (relationship lending).
  - Large firms (top 20 percentile, Number of Firms: 105):
    - MPI_t for DEBT: 1.436 (0.37); for BANK: -4.882 (0.02); MPI_t-1 for BANK: 4.435 (0.00).
    - Evidence: immediate decline in bank debt followed by later increase (lagged renegotiation).
  - Listed status within size: large listed firms borrowed more; small listed firms' response muted.
- Leverage-based sub-samples (top 20% vs bottom 20% by DEBT):
  - Highly leveraged firms (top 20 percentile, Number of Firms: 105):
    - MPI_t for DEBT: 1.959 (0.00); for STBANK: 3.278 (0.00); MPI_t-1 for DEBT: 2.624 (0.00).
    - Highly leveraged firms increased overall and bank debt with a strong positive lagged response.
  - Low-leverage firms (bottom 20 percentile):
    - MPI_t for DEBT: 1.794 (0.00); MPI_t-1 for DEBT: 2.316 (0.00).
    - Low-leverage firms exhibited lagged reductions in bank debt after contraction in some specifications.

### VI. Interpretation and implications
- Dual-channel evidence:
  - Interest-rate channel: immediate reductions in overall and bank debt after monetary tightening indicate strengthened interest-rate transmission since 1998.
  - Relationship lending: listed firms and some small/leveraged firms maintain or increase short-term bank borrowing to preserve bank relationships even when other finance is available.
- Financial-stability implications:
  - Corporate deleveraging followed by re-leveraging has implications for adverse selection and moral hazard.
  - Corporate balance sheets matter for financial stability; authors recommend incorporating corporate balance-sheet dynamics into financial stability analysis (explicit stability analysis left for future research).

### VII. Concise statement of main results (authors' summary)
- First: firms lower total debt and bank debt immediately following monetary tightening; lagged response tends to raise debt.
- Second: private corporates’ response is more muted than public firms, though private firms reduce bank debt.
- Third: listed firms tend to increase overall debt in response to monetary tightening, driven by increases in short-term bank borrowings.
- Fourth: the response was muted in 1992-97 and more pronounced in 1998-2003 (immediate lowering of debt and later re-leveraging).
- Fifth: split by firm size indicates relationship lending with a lagged response for large firms; small firms often increase bank debt.
- Sixth: by leverage, private firms exhibit relationship lending vis-à-vis their public counterparts.

### VIII. Key statistics and diagnostics (selected exact figures)
- Sample size: 525 firms; time period: 1992-2003.
- Fixed-effects whole-sample diagnostics:
  - R-square: 0.37 (DEBT); 0.30 (BANK); 0.29 (STBANK).
  - Number of Observations: 5166 (DEBT), 5107 (BANK), 4946 (STBANK).
- Selected coefficients (whole sample, p-Values in brackets):
  - TAN on DEBT: 0.095 (0.00).
  - SIZE on DEBT: 0.375 (0.04).
  - DEPCN on DEBT: -0.883 (0.00).
  - DIVI on DEBT: -0.878 (0.00).
  - MPI_t on DEBT: -3.392 (0.06); MPI_t-1 on DEBT: 1.153 (0.01).
- External financing pattern (aggregate averages for 1992-2002, PERCENT OF TOTAL):
  - Paid-up capital: 18.411.628.830.2
  - Long-term debt: 14.49.77.66.3
  - Short-term debt: 34.244.728.625.5
  - of which working capital: 15.716.618.615.6
  - Memo — Bank Debt: 42.944.918.514.8

*Source: _wp0525 - 8. Response of Firms to Monetary Contraction: Summary Features (PDF chapter), 1992–2003 sample, Prowess database (CMIE), sample of 525 manufacturing firms.*

### References..............................................................................................................

### _wp0525 - References..............................................................................................................

### References section
- Title: References.............................................................................................................................. 16

### Tables listed in the References unit
- 1. Distribution of Sample Firms by Industry Classification .......................................... 19
- 2. Breakdown of Sample Firms by Ownership and Industry Type................................ 20
- 3. External Financing Pattern by Governance Type ...................................................... 20
- 4. Correlation Matrix Among the Variables .................................................................. 21
- 5. Fixed-Effects Estimation for the Whole Sample ....................................................... 22
- 6. Fixed-Effects Estimation for the Sub-Periods–Select MPI Coefficients ..................... 23
- 7. Fixed-Effects Estimation for Four Sub-Samples–Select MPI Coefficients................. 24

*Source: _wp0525 - References..............................................................................................................*

### 8. Response of Firms to Monetary Contraction: Summary Features............................. 25

### 8. Response of Firms to Monetary Contraction: Summary Features

### I. Introduction and purpose
- Objective: Investigate the association between corporate finance and monetary policy in India over the period 1992 to 2003 using firm-level data, distinguishing firms by ownership and governance, and across sub-periods.
- Conceptual context:
  - Two corporate finance paradigms referenced: Modigliani-Miller (financing choice irrelevant in perfect markets) and the pecking-order (internal finance preferred; debt over equity).
  - Two monetary transmission views: credit view (bank-dependent firms more affected by monetary tightening) and relationship lending (long-term bank–firm relationships mitigate cyclical loan supply changes).
- Data scope: manufacturing firms maintaining identity and reporting annual accounts without gaps for 1992 through 2003; final sample size: 525 firms.

### II. Data and institutional background
- Data source: Prowess database (Release 2.1) maintained by CMIE.
- Inclusion thresholds and definitions:
  - Database contains financial information on over 8,000 companies, including listed and major unlisted public limited companies having sales in excess of Rs.10 million.
  - Unlisted entities qualify if average sum of sales and total assets ≥ Rs.200 million (latest audited results).
  - USD 1≈Rs.45.
  - Private company criteria include minimum paid-up capital of Rs.0.1 million; public company minimum paid-up capital Rs.0.5 million.
  - Listing on the Mumbai Stock Exchange: minimum paid-up equity capital not less than Rs.100 million; post-issue capitalization not lower than Rs.200 million. For listed companies considered, minimum market capitalization should be Rs.500 million and post-issue net worth should be Rs.200 million.
- Sample composition notes:
  - Around 33 percent of firms are in chemicals, machinery and textile sectors.
  - About 5 per cent of companies in the sample are public; they account for nearly 27 per cent of total assets of firms.
  - Over 80 percent of private firms in the sample are listed.
- Financial sector reform context:
  - Pre-1992: strong constraints on equity access (Controller of Capital Issues) and long-term debt largely via development banks.
  - 1991–1997 reforms included heavy statutory preemptions (example: commercial banks had to hold as much as 63.5 per cent of increases in deposits in cash reserves and government debt instruments; 40 percent of credit to designated priority sectors).
  - 1992: CCI abolished; freer access to capital markets under SEBI oversight.
  - 1997: Bank Rate activated as signaling rate; statutory pre-emption on bank deposits gradually lowered; since April 1, 1997, automatic monetization replaced by Ways and Means Advances (WMA).

### III. Empirical strategy and variables
- Estimation framework: panel regression with fixed effects, time dummies included; primary reduced-form specification:
  - Yit = α*Xit + β1*MPIt + β2*MPIt-1 + γ*MPIt*LISTEDt + eit
  - Fully specified (controls): INT, TAN, SIZE (log total assets), AGE (years since incorporation), DEPCN, EARN, RND, DIVI; interactions with PRIVATE and LISTED dummies; industry dummies.
- Dependent variables (three debt ratios):
  - DEBT = total borrowing to total assets.
  - BKDEBT = bank borrowing to total borrowing.
  - STBANK = short-term bank borrowing to total bank borrowing.
- Monetary policy indicator (MPI): natural logarithm of the yield on 364-day treasury bills (primary market cut-off yield used).

### IV. Key empirical findings
- Correlations:
  - DEBT and its components are positively correlated with each other and negatively correlated with most control variables.
  - Monetary policy indicator is negatively correlated with debt components (firms tend to reduce debt following monetary tightening).
- Control variables (sign and intuition):
  - INT (interest expense to total earnings): higher INT associated with higher debt levels, but linked to lower short-term bank debt.
  - TAN (tangible assets/total assets): positive relationship with debt (collateral reduces informational asymmetry).
  - SIZE: positive relationship with overall debt; negative relationship with short-term bank debt (small firms use more short-term debt).
  - DEPCN: negative coefficient (large non-debt tax shield reduces incentive to use debt).
  - AGE: positively related to debt.
  - EARN: negative coefficient (higher earnings reduce need for external debt).
  - DIVI: negative coefficient (dividend payment and debt act as substitutes in agency models).
  - RND: negative coefficient (firms with more R&D are less leveraged).
- Monetary policy effects (overall sample):
  - Contemporaneous impact of monetary tightening: significant and negative on bank debt (firms reduce total debt and bank debt immediately).
  - Lagged impact: positive in DEBT and BKDEBT specifications (over the medium term firms increase bank borrowings after initial cutback).
  - Short-term vs long-term bank debt: immediate lowering of short-term bank debt relative to long-term bank debt; later renegotiation leads to increased bank debt.
- Ownership and governance differentials:
  - Private vs public: private firms are proactive in lowering bank debt relative to public counterparts on monetary tightening, but overall response muted.
  - Listed vs unlisted: listed firms increase overall debt by increasing short-term bank borrowing after monetary tightening—consistent with relationship lending (maintaining bank credit lines despite access to non-bank finance). Alternative interpretation: listed firms anticipate interest rate hikes and increase debt accordingly.

### V. Heterogeneity across periods, size, and leverage
- Sub-periods: split into 1992-97 and 1998-03.
  - 1992-97: monetary policy had limited contemporaneous effect; lagged effect more pronounced (contraction lowered overall debt and short-term bank debt with a lag); corporate responses largely muted and similar across ownership/governance.
  - 1998-03: contractionary monetary policy had both contemporaneous and lagged impact—lowering overall debt immediately and raising it subsequently; private firms actively lowered debt (especially bank debt); listed firms increased bank borrowing to maintain relationship lending.
- Firm size (top 20% vs bottom 20% of size distribution):
  - Large firms: immediate decline in bank debt followed by later increase (lagged adjustment).
  - Small firms: increased overall debt and bank debt in response to monetary tightening—evidence supporting relationship lending for small firms; lagged effects limited.
  - Large private firms lowered bank debt relative to public counterparts; small firms tended to lower overall debt (effect on bank debt unclear).
  - Large listed firms borrowed more; small listed firms' response muted.
- Leverage (top 20% vs bottom 20% by DEBT):
  - Highly leveraged firms: increased overall debt and increased bank debt with a strong positive lagged response.
  - Low-leverage firms: exhibited a lagged reduction of bank debt after monetary contraction.
  - Private highly leveraged firms accumulated more bank debt relative to highly leveraged public firms, mainly via short-term bank debt.
  - Listed highly leveraged firms exhibited limited response; listed low-leverage firms reduced bank debt after tightening.

### VI. Interpretation and implications
- Evidence supports both the interest-rate (interest rate transmission) channel and relationship lending:
  - Interest-rate channel: immediate reductions in overall and bank debt after monetary tightening indicate strengthened interest-rate transmission since 1998.
  - Relationship lending: listed firms and some small/leveraged firms maintain or increase short-term bank borrowing to preserve bank relationships even when other finance is available.
- Corporate balance sheets matter for financial stability: corporate deleveraging and subsequent re-leveraging patterns have implications for adverse selection and moral hazard; corporate balance sheets should be incorporated into financial system stability analysis (explicit stability analysis left for future research).

### VII. Concise statement of main results (authors' summary)
- First: firms lower total debt and bank debt immediately following monetary tightening; lagged response tends to raise debt.
- Second: private corporates’ response is more muted than public firms, though private firms reduce bank debt.
- Third: listed firms tend to increase overall debt in response to monetary tightening, driven by increases in short-term bank borrowings.
- Fourth: the response was muted in 1992-97 and more pronounced in 1998-2003 (immediate lowering of debt and later re-leveraging).
- Fifth: split by firm size indicates relationship lending with a lagged response for large firms; small firms often increase bank debt.
- Sixth: by leverage, private firms exhibit relationship lending vis-à-vis their public counterparts.

*Source: _wp0525 - 8. Response of Firms to Monetary Contraction: Summary Features (PDF chapter), 1992–2003 sample, Prowess database (CMIE), sample of 525 manufacturing firms.*

### References

### _wp0525 - References

### References (selected)
- Aksoy, Y., and M.A. Leon-Ledesma (2004). “Interest Rates and Output in the Long Run. Keynes College.” Canterbury, UK (mimeo).
- Bernanke, B.S., and A.S. Blinder (1992). “The Federal Funds Rate and the Channels of Monetary Transmission.” American Economic Review, 82, 4, 901-27.
- Bernanke, B.S. and M.Gertler (1995). “Inside the Black Box: The Credit Channel of Monetary Policy Transmission.” Journal of Economic Perspectives, 9(1), 27-48.
- Calvo, G. and C. Reinhart (2002). “Fear of Floating.” Quarterly Journal of Economics. 117 (2), 379-408.
- Centre for Monitoring of Indian Economy. Prowess (Release 2.1), CMIE: Mumbai.
- Chibber, P.K., and S.K.Majumdar (1999). “Foreign Ownership and Profitability: Property Rights, Control, and the Performance of Firms in Indian Industry.” Journal of Law and Economics, 42 (1), 209-238.
- Cobham, D., and R.Subramaniam (1998). “Corporate Finance in Developing Countries: New Evidence for India.” World Development, 26 (6), 1033-1047.
- Davis, E.P., and M.R. Stone (2004). “Corporate Finance and Financial Stability.” IMF Working Paper No. 124 (Washington: International Monetary Fund).
- de Haan, L and E.Sterken (2000). “Capital Structure and Corporate Governance: Evidence from Euro Area.” (Unpublished; Antilles: De Nederlandes Bank).
- Dedola, L., and F.Lippi (2000). “The Monetary Transmission Mechanism: Evidence from the Industries of Five OECD Countries.” (Unpublished; Rome: Bank of Italy).
- Ehrmann, M., (2000). “Firm Size and Monetary Policy Transmission: Evidence from German Business Survey Data.” European Central Bank Working Paper No.21, Frankfurt.
- Ganley, J., and C.Salmon (1997). “The Industrial Impact of Monetary Policy Shocks: Some Stylized Facts. Bank of England Working Paper No. 68, Bank of England: UK.
- Huisman, J., and N. Hermes (1997). “Financial Liberalization in India and the Impact on the Business Environment.” International Journal of Development Banking, 15 (1), 3-14.
- Jalan, B., (2002). “Corporate Governance and Financial Sector: Some Issues.” Inaugural Address at NIBM Annual Day, NIBM: Pune.
- Jena, P.R., K.N. Murty, and V. Narasimhan (2004). “Integration of Financial Markets in India: An Empirical Analysis.” Paper presented at the Sixth Annual Conference on Money and Finance, IGIDR, Mumbai.
- Kashyap, A.K., and J.C. Stein (1997). “What do a Million Banks have to say about the Transmission of Monetary Policy?” NBER Working Paper No.6056 (Cambridge, Massachusetts: National Bureau of Economic Research).
- Kashyap, A.K, J.C.Stein and D.W.Wilcox (1993). “Monetary Policy and Credit Conditions: Evidence from the Composition of External Finance.” American Economic Review, 83 (1), 73-98.
- Kashyap, A.K., J.C. Stein and D.W. Wilcox (1996). “Monetary Policy and Credit Conditions: Evidence from the Composition of External Finance: Reply.” American Economic Review, 86 (2), 310-314.
- Khanna, T., and K. Palepu (2000). “Is Group Affiliation Profitable in Emerging Markets: An Analysis of Diversified Indian Business Groups?” Journal of Finance, 55 (2), 867-891.
- Kroszner, R.S., and P.E. Strahan (2001). “Bankers on Boards: Monitoring, Conflicts of Interests and Lender Liability.” Journal of Financial Economics, 62 (3), 415-452.
- Majumdar, S.K., (1997). “The Impact of Size and Age on Firm-Level Performance: Some Evidence from Indian Industry.” Review of Industrial Organisation, 12 (2), 231-241.
- Miller, M.H., and K. Rock (1985). “Dividend Policy under Asymmetric Information.” Journal of Finance, 40 (4), 1031-1051.
- Mizen, P., and C. Yalcin (2002). “Corporate Finance when Monetary Policy Tightens: How Do Banks and Non-Banks Affect Access to Credit?” Working paper No.18, Experian Centre for Economic Modelling, University of Nottingham, UK.
- Modigliani, F., and M.H. Miller (1958). “The Cost of Capital, Corporation Finance and the Theory of Investment.” American Economic Review. 48, 261-297.
- Myers, S.C., and N. Majluf (1984). “Corporate Financing and Investment Decisions when Firms Have Information Investors Do Not Have.” Journal of Financial Economics, 13 (1), 187-221.
- Oliner, S.D., and G.D. Rudebusch (1996). “Is There a Broad Credit Channel for Monetary Policy?” Federal Reserve Bank of San Francisco Economic Review, 1, 4-13.
- Rajan, R.G., (1992). “Insiders and Outsiders: The Choice between Informed and Arms-Length Debt.” Journal of Finance, 47, 1367-1400.
- Rangarajan, C., (1988). “Issues in Monetary Management.” Presidential Address at the 71st Conference of Indian Economic Association, Delhi.
- Reddy, Y.V., (2002). “Parameters of Monetary Policy in India.” Lecture Delivered at the 88th Annual Conference of Indian Econometric Society, Chennai.
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### Sample and Industry Distribution (Table 1)
- Heavy industries: 468.8 (Number of Firms / Percent of total appear as combined in source)
- Drugs and pharmaceuticals: 499.3
- Chemicals: 6612.6
- Cement: 183.4
- Textile and textile products: 529.9
- Auto ancillaries: 468.8
- Food and beverages: 356.7
- Electrical machinery: 6211.8
- Diversified: 254.8
- Others: 12624.0
- Total: 525100.0
- Source: Compiled from Prowess database.

### Ownership and Listing Breakdown (Table 2)
- Table reports counts by Industry group for Public Companies, Private Companies, and totals with columns "Of which listed" preserved in layout.
- Examples from table entries (preserved exactly as in source):
  - Heavy industries: 6 2403146 33
  - Drugs and pharmaceuticals: 1 0483749 37
  - Chemicals: 7 3595166 54
  - Cement: 0 0181718 17
  - Textile and textile products: 0 0524752 47
  - Auto ancillaries: 1 1454246 43
  - Food and beverages: 0 0353235 32
  - Electrical Machinery: 2 1605462 55
  - Diversified: 0 0251925 19
  - Others: 7 311992126 95
  - TOTAL: 24 10501422525 432
- Source: Compiled from Prowess data base.

### External Financing Patterns by Listing (Table 3) — Aggregate averages for 1992-2002 (PERCENT OF TOTAL)
- Paid-up capital: 18.411.628.830.2
- Long-term debt: 14.49.77.66.3
- Short-term debt: 34.244.728.625.5
- of which working capital: 15.716.618.615.6
- Memo — Bank Debt: 42.944.918.514.8
- Source: Authors’ calculations.

### Correlation Matrix among Variables (Table 4)
- Variables and select correlations (exact figures preserved):
  - DEBT with BANK: -0.284
  - DEBT with STBANK: -0.125
  - INT with DEBT: 0.240
  - TAN with DEBT: 0.276
  - SIZE with DEBT: 0.076
  - DEPCN with DEBT: 0.177
  - EARN with DEBT: -0.284
  - RND with DEBT: -0.021
  - DIVI with DEBT: -0.289
  - AGE with DEBT: 0.005
  - MPI correlations included (see source)
- Note: Monetary policy indicator is proxied by 364-day t-bill yield.
- Variable definitions: DEBT = aggregate borrowing/total asset; BANK = bank borrowing/total borrowing; STBANK = short-term bank borrowing/total bank borrowing; INT = interest expense/total earnings; TAN = tangible asset / total asset; SIZE = logarithm of total asset; AGE = number of years since the incorporation of the firm; DEPCN = depreciation; EARN = operating income; RND = Research and development expenses/Sales; DIVI = dividend payment/ net operating income.

### Fixed-Effects Estimation — Whole Sample (Table 5)
- Dependent variables: DEBT, BANK, STBANK
- Control variables with coefficients and p-values (p-Values in brackets):
  - INT: 0.143 (0.04) for DEBT; -0.011 (0.80) for BANK; -0.069 (0.00) for STBANK
  - TAN: 0.095 (0.00); 0.233 (0.00); 0.195 (0.00)
  - SIZE: 0.375 (0.04); -0.358 (0.00); -1.841 (0.00)
  - DEPCN: -0.883 (0.00); -0.341 (0.27); -0.318 (0.36)
  - EARN: -0.505 (0.00); -0.156 (0.01); -0.022 (0.37)
  - AGE: 2.234 (0.06); -0.248 (0.09); 0.837 (0.17)
  - DIVI: -0.878 (0.00); -1.064 (0.00); -0.993 (0.00)
  - RND: -0.136 (0.12); -0.099 (0.11); -0.228 (0.00)
- Monetary Policy Indicator:
  - MPI_t: -3.392 (0.06) for DEBT; -2.744 (0.02) for BANK; -1.892 (0.10) for STBANK
  - MPI_t-1: 1.153 (0.01); 1.042 (0.09); 0.473 (0.50)
- Interaction terms:
  - MPI_t * PRIVATE_t: -0.671 (0.58); -1.284 (0.09); 0.520 (0.19)
  - MPI_t * LISTED_t: 1.564 (0.07); 1.048 (0.49); 1.873 (0.09)
- Diagnostics:
  - R-square: 0.37 for DEBT; 0.30 for BANK; 0.29 for STBANK
  - Number of Observations: 5166 (DEBT), 5107 (BANK), 4946 (STBANK)
  - Number of Firms: 525 (for all)
  - Time period: 1992-2003 (for all)
- Note: PRIVATE = 1 for private firms, 0 for public firms. LISTED = 1 for firms listed on the Mumbai Stock, Mumbai, 0 for unlisted firms.

### Fixed-Effects Estimation — Sub-periods (Table 6) — Select MPI Coefficients
- Sub-period 1: 1992-97
  - DEBT MPI_t: -1.135 (0.87)
  - BKDEBT MPI_t: 1.618 (0.17)
  - STBANK MPI_t: 1.563 (0.31)
  - DEBT MPI_t-1: -1.796 (0.00)
  - BKDEBT MPI_t-1: 1.161 (0.00)
  - STBANK MPI_t-1: -1.503 (0.09)
  - Diagnostics: R-square = 0.43 (DEBT), 0.40 (BKDEBT), 0.36 (STBANK)
  - No. of Observations: 2375 (DEBT), 2347 (BKDEBT), 2256 (STBANK)
  - No of Firms: 525 (all)
- Sub-period 2: 1998-2003
  - DEBT MPI_t: -1.355 (0.10)
  - BKDEBT MPI_t: -2.955 (0.07)
  - STBANK MPI_t: 1.366 (0.10)
  - DEBT MPI_t-1: 1.973 (0.00)
  - BKDEBT MPI_t-1: 1.001 (0.05)
  - STBANK MPI_t-1: 1.739 (0.21)
  - Diagnostics: R-square = 0.58 (DEBT), 0.40 (BKDEBT), 0.38 (STBANK)
  - Number of Observations: 2326 (DEBT), 2303 (BKDEBT), 2248 (STBANK)
  - Number of Firms: 525 (all)
- Note: p-Values in brackets. MPI is proxied by 364-day T-Bill yield.

### Fixed-Effects Estimation — Four Sub-samples (Table 7) — Select MPI Coefficients
- Sub-sample 1: Small firms (bottom 20 percentile with respect to SIZE), Number of Firms: 105, Period: 1992-2003
  - MPI_t: 0.660 (0.10) for DEBT; 0.319 (0.06) for BANK; -0.378 (0.10) for STBANK
  - MPI_t-1: 1.371 (0.19); 1.332 (0.31); 2.187 (0.12)
  - MPI_t * PRIVATE_t: -1.749 (0.07); 1.814 (0.29); 0.345 (0.81)
  - MPI_t * LISTED_t: 0.761 (0.22); -1.008 (0.35); -1.269 (0.27)
  - R2: 0.43 (DEBT); 0.23 (BANK); 0.18 (STBANK)
- Sub-sample 2: Large firms (top 20 percentile with respect to SIZE), Number of Firms: 105, Period: 1992-2003
  - MPI_t: 1.436 (0.37); -4.882 (0.02); 3.350 (0.74)
  - MPI_t-1: -2.844 (0.19); 4.435 (0.00); 4.261 (0.00)
  - MPI_t * PRIVATE_t: 0.784 (0.40); 2.436 (0.06); -0.593 (0.76)
  - MPI_t * LISTED_t: 0.642 (0.10); -0.097 (0.19); -1.004 (0.35)
  - R2: 0.51; 0.24; 0.27
- Sub-sample 3: Low-leveraged firms (bottom 20 percentile with respect to DEBT), Number of Firms: 105/105/242 (DEBT/BANK/STBANK)
  - MPI_t: 1.794 (0.00); -1.309 (0.36); -1.740 (0.16)
  - MPI_t-1: 2.316 (0.00); 2.243 (0.12); 3.548 (0.00)
  - MPI_t * PRIVATE_t: -0.061 (0.58); -2.229 (0.39); -1.093 (0.64)
  - MPI_t * LISTED_t: -0.049 (0.38); 0.069 (0.58); 0.720 (0.08)
  - R2: 0.26; 0.24; 0.29
- Sub-sample 4: High-leveraged firms (top 20 percentile with respect to DEBT), Number of Firms: 105 (each)
  - MPI_t: 1.959 (0.00); -1.143 (0.22); 3.278 (0.00)
  - MPI_t-1: 2.624 (0.00); 1.767 (0.03); -2.769 (0.00)
  - MPI_t * PRIVATE_t: 0.106 (0.57); 1.437 (0.03); 0.428 (0.01)
  - MPI_t * LISTED_t: 0.068 (0.55); -0.792 (0.30); -1.269 (0.20)
  - R2: 0.31; 0.27; 0.26
- Note: p-Values in brackets. MPI is proxied by 364-day T-Bill yield.

### Summary of Firms' Response to Monetary Contraction (Table 8)
- Whole Sample:
  - DEBT: MPI — Negative; Lagged MPI — Positive
  - BKDEBT: MPI — Negative; Lagged MPI — Positive
  - STBANK: MPI — Negative; Lagged MPI — RL
  - Ownership: Negative
  - Listed: Positive (DEBT), Positive (STBANK)
- Sub-period 1:
  - Lagged MPI: Negative (DEBT), Positive (BKDEBT), Negative (STBANK)
- Sub-period 2:
  - DEBT: MPI — Negative; Lagged MPI — Positive
  - BKDEBT: MPI — Negative; Lagged MPI — Positive
  - STBANK: MPI — Positive; Ownership effects: Negative for DEBT and BKDEBT, Positive for STBANK
  - Listed: Positive (DEBT and BKDEBT), Negative (STBANK) RL
- Large Firms:
  - MPI effects primarily Negative for BKDEBT; Lagged MPI Positive for DEBT and BKDEBT; Listed: Positive
- Small Firms:
  - MPI: Positive for DEBT and BKDEBT; Negative for STBANK; RL noted
  - Ownership: Negative
- Highly-leveraged Firms:
  - MPI: Positive for DEBT and STBANK; Lagged MPI Positive; Ownership: Positive for DEBT and BKDEBT; RL noted
- Firms with Low-leverage ratios:
  - MPI: Positive for DEBT
  - Lagged MPI: Positive for DEBT and BKDEBT
  - Ownership: Positive for BKDEBT and STBANK; RL noted
- Note: RL denotes relationship lending.

*_Source: _wp0525 - References (compiled from the source PDF)._

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_Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2005/_wp0525.pdf_