Table 5. Bank Lending Relationship by Bank Type and Firm Size and Industry

||S|mall Ban|ks|L|arge Ban|ks|Pro|fitable Ba|nks|St|able Ban|ks|L|iquid Ban|ks|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|Loans granted by firm size|Freq.|Percent|Cum.|Freq.|Percent|Cum.|Freq.|Percent|Cum.|Freq.|Percent|Cum.|Freq.|Percent|Cum.|
|Small|29,915|41.7|41.7|6,786|62.7|62.7|963|38.2|38.2|7,661|37.9|37.9|7,778|38.4|38.4|
|Medium|32,274|45.0|86.7|3,151|29.1|91.8|1,352|53.7|91.9|10,346|51.1|89.0|10,259|50.6|89.0|
|Large|9504|13.3|100.0|884|8.2|100.0|204|8.1|100.0|2236|11.1|100.0|2222|11.0|100.0|
|Total|71,693|100||10,821|100||2,519|100||20,243|100||20,259|100||
||S|mall Ban|ks|L|arge Ban|ks|Pro|fitable Ba|nks|St|able Ban|ks|L|iquid Ban|ks|
|Loans granted by firm<br>industry|Freq.|Percent|Cum.|Freq.|Percent|Cum.|Freq.|Percent|Cum.|Freq.|Percent|Cum.|Freq.|Percent|Cum.|
|Food processing|13,267|18.5|18.5|1,512|14.0|14.0|524|20.8|20.8|4,727|23.4|23.4|4,769|23.5|23.5|
|Textiles|8,349|11.7|30.2|673|6.2|20.2|405|16.1|36.9|2,970|14.7|38.0|3,526|17.4|40.9|
|Garments|8,340|11.6|41.8|1,543|14.3|34.5|319|12.7|49.5|2,493|12.3|50.3|2,938|14.5|55.5|
|Shoes and leather products|4,026|5.6|47.4|1,325|12.2|46.7|157|6.2|55.8|1,471|7.3|57.6|1,587|7.8|63.3|
|Chemicals|6,791|9.5|56.9|664|6.1|52.8|230|9.1|64.9|1,366|6.8|64.4|1,252|6.2|69.5|
|Machinery|7,440|10.4|67.3|1,272|11.8|64.6|182|7.2|72.1|2,401|11.9|76.2|1,924|9.5|79.0|
|Electronics|9,514|13.3|80.5|1,252|11.6|76.2|339|13.5|85.6|1,368|6.8|83.0|1,117|5.5|84.5|
|Auto-parts|3,617|5.1|85.6|863|8.0|84.1|68|2.7|88.3|1,125|5.6|88.5|856|4.2|88.7|
|Furniture|10,349|14.4|100.0|1,717|15.9|100.0|295|11.7|100.0|2,322|11.5|100.0|2,290|11.3|100.0|
|Total|71693|100||10821|100||2519|100||20243|100||20259|100||

# **5. Empirical Results**

While the ICA-survey shows the problems of firms in accessing external financing relative to other constraints, they suffer from the endogeneity problems mentioned, e.g., we do not know the real reasons for the mentioned obstacles, including lack of external financing. It can be that the firm indeed has good growth opportunities, but banks are not interested in lending to firms in general. Or it can be that the banks make the right judgment in not lending as the firm has limited growth opportunities or is not creditworthy. We can now use the data to more formally assess the demand of the borrower and the supply of banks to provide financing as a function of the financing terms as well as various macro and micro variables including firms and bank characteristics. We estimate a disequilibrium model described in equations (1) to (8), where the set of explanatory variables for loan demand include the set of firm and loan characteristics, macro-economic variables such as measures of inflation and growth and represents a set of banks and loan characteristics and macroeconomic variables.

The dependent variable is the value of the contracted loan. The coefficients (betas) represent by how much the amount of a loan increases by increasing one of the regressors. The estimates rely on the disequilibrium model as in Madalla (1974). Since we are estimating 2 equations (demand and supply), supply betas are the estimates for the supply coefficients and demand betas are the estimates for the demand coefficients. The estimation is Bayesian using a quadratic loss function and the posterior was calculated using the Metropolis Hasting's procedure. For each issue we first present the OLS estimates and then the disequilibrium results.

# **Determinants of Firms’ Demand for Bank Financing**

Table 6.A. shows the results of the OLS estimation of the demand for each type of loan and for all loans together. With respect to the loan demand, the lending rate has the expected negative sign in most of the estimations and is significant. The exceptions are working capital and vendor loans. However, the lending rates coefficients coming from the working capital estimations are not significant. The results show that the maturity of the loans has a positive and significant effect on loan demand overall. Also, firms that can provide collateral have a higher demand for credit. The table suggests that macroeconomics variables, such as inflation and GDP 17