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Bank ownership and firm performance

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Does a bank’s ownership matter for the performance of a firm to which it is connected, especially in the event of a crisis? Pavel Chakraborty discusses the effect of the 2008–9 crisis on Indian manufacturing firms to provide evidence on a new channel that can matter significantly for a firm’s performance—bank ownership.

Image courtesy of interviewee. June 5, 2024

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This video discusses a research study examining the impact of bank ownership on firm performance, particularly in the context of the 2008 financial crisis. It highlights studies from Brazil and India that illustrate how regions with a higher proportion of public sector banks fared better during the crisis in terms of employment and GDP. This video raises questions about how different types of banks affect the credit available to connected firms, thus influencing their performance.

The speaker reviews existing literature on the importance of banks to firm performance, referencing historical examples, such as the Great Depression, as well as recent studies demonstrating the role of bank health in export performance. The research emphasizes the differential effects that public and private sector banks have on credit distribution and firm performance during economic shocks.

The methodology involves analyzing data from a dataset called Prowess, which provides comprehensive financial information about Indian firms and their banking relationships. The study employs a difference-in-difference approach to compare the effects on firms connected to public vs. private banks during and after the financial crisis, with findings suggesting that firms linked to public banks faced less credit reduction and better performance metrics.

Results indicated that firms connected to private banks received about 15% less credit and realized around 25% lower export earnings compared to those linked to public banks, underscoring the critical role banks play during economic downturns. The study also identifies variations based on firm size and sector, and notes that firms part of business groups experienced mitigated impacts due to internal capital markets.

This video concludes with suggestions for further research, focusing on the implications of supporting inefficient firms during crises and the broader effects of such policies on economic productivity and capital allocation.

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Here are five key points from the video:

1. **Differential Impact of Public and Private Sector Banks**: The video discusses how research studies from Brazil and India show that during financial crises, regions with a higher proportion of public sector banks experience more positive outcomes in terms of employment and GDP compared to those with private sector banks. In India, firms connected to public sector banks showed different performance metrics than those connected to private sector banks during financial turbulence.

2. **Importance of Bank Health for Firm Performance**: The video highlights literature indicating that the health of banks, including their capacity to provide credit, directly impacts firms' performance, especially their export abilities. There are references to studies examining how banking relationships affect firm performance, particularly during economic crises.

3. **Micro-Level Data Analysis**: The author emphasizes the necessity of micro-level datasets, like the Prowess dataset, which tracks detailed credit relationships and balance sheet information of firms and banks over time. This granular data enables researchers to analyze the effects of bank ownership on firm performance during crises.

4. **Methodological Approach**: The analysis employs a difference-in-difference methodology, comparing the performance of firms linked with public and private banks before and after a financial crisis. The approach aims to uncover how the differential impacts of bank ownership translate into variations in firm performance metrics such as sales, credit received, and export volumes.

5. **Future Research Directions**: The video suggests areas for future research, including exploring whether public sector banks protect inefficient firms at the expense of reallocating resources away from potentially more productive enterprises. This misallocation problem could exacerbate overall economic inefficiency and hinder productivity growth in the aftermath of financial shocks.

Overall, these points encapsulate the core themes regarding the relationship between bank types, firm performance during crises, and the implications for future economic analysis.

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Here are some key quotes from the video you , centered around the role of banks in firm performance and the impact of the financial crisis:

1. **On the importance of banks for firm performance:**
- "Given kind of these two studies, it get me kind of thinking that whether since the banks are differentially affected, what happened to the firms which are kind of associated to these banks..."

2. **Economic impact during financial crises:**
- "...the regions in Brazil, which have higher proportion of public sector banks... during the financial crisis had a higher impact or positive impact in terms of employment, uh, um, local GDP…"

3. **Historical convideo of banking and firm performance:**
- "There are three kinds of literature overall... which talks about how banks are very important for performance."

4. **On the correlation between bank health and firm exports:**
- "If the bank's health or banks' credit is very good, and the firms connected to those banks perform very good,..."

5. **Differential impact of bank types on firms during crises:**
- "...the banks in India, that the private sector banks and the public sector banks are differentially affected during the crisis."

6. **Financial shocks and global integration:**
- "...how financial shocks are propagated to banking channels because of global integration."

7. **The relevance of the 2008 financial crisis:**
- "...the financial sector shock during the 2008, was really important for this going down of trade..."

8. **Analyzing firm-bank relationships:**
- "...this dataset is important in this case? Is there, it comes up with a few unique features of this dataset."

9. **On methodology for analysis:**
- "I employ a very standard... difference in difference methodology."

10. **Findings on credit access and performance:**
- "...the firms which are connected to the private banks are getting... about 15% less credit..."

11. **The quantitative impact on sales and exports:**
- "Firms which are connected to public sector banks are earning 25% more than the firms which are connected to the private sector banks."

12. **Concerns about long-term economic implications:**
- "If the public sector banks are protecting those firms which are not supposed to be protected, then it's kind of a step in the dark in a sense."

These quotes encapsulate the main arguments and findings of the discussion, highlighting the significance of different bank ownership structures and their impact on firm performance, especially during economic crises.

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When I was kind of doing a research for this

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or understanding how banks could matter

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for foreign performance, two kind

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of studies caught my attention.

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One was in Brazil and one was India.

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And this kind of, caught out

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after the financial crisis of 2008.

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They were showing that especially in Brazil,

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that the regions in Brazil, which have higher proportion

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of public sector banks, compared to private banks,

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those regions during the financial crisis had a higher

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impact or positive impact in terms of employment,

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local GDP, et cetera.

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And also on the other side, there are one study which shows

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that the banks in India, that the private sector banks

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and the public sector banks are

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differentially affected during the crisis.

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So given kind of these two studies, it get me kind

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of thinking

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that whether since the banks are differentially affected,

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what happened to the firms which are kind of a associated

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to these banks, whether these firms

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getting credit from these banks could be differentially

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impacted because the banks

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themselves are differentially impacted.

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So these two studies, let me think about whether,

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or let me get deep about whether firms are getting impacted

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due to, and whether ownership in this case

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and actually playing a role help form performance in terms

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terms of their overall performance,

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sales export, et cetera, et cetera.

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There are three kinds of literature overall.

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One in, in very recent, one actually that starts

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with mental Friedman books in 1969

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and, which talks about how banks are very important

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for, for performance.

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And they kind of talk about, during the Great Depression

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of 19 20 19, 19 33, showing that how firms,

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because how firms, how banks were helping firms

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in coming out of the depression during, in

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and especially in the United States

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during the Great Depression of 1929 to 33.

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And there were subsequent studies, especially in the recent,

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recent couple of last couple of decades showing

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that banks are very important for foreign performance.

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Like there is a paper in Japan, for Japan,

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which came out in quarterly Journal of Economics,

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which shows that the bank health is very important

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for form exports.

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If the bank's health or banks, credit is very good.

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And the forms connected to those banks perform very good,

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especially in terms of,

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in the exports market in the world market.

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So this is one part of the literature that talks about

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bank health is very important for foreign performance.

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And these papers are in the recent era. Why?

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Because this is for this, you need very micro level of data,

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like knowing which are the banks

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connected to which of the firms.

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And in the, in the couple of last couple

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of tickets we have kind of coming out

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of micro level data sets

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where we can really go into these data sets to understand

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how banks are important for foreign performance.

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There's this other study set of studies which talks about

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how financial shocks are propagated to banking channels

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because of global integration.

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And there was a study, very interesting study in,

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published in Journal of Financial Economics, which,

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which talks about, how forms

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which were connected to the banks, which were dependent,

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which were affected due to the crisis, the Russian crisis,

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1998, and opposed to forms which on public debt.

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And they show that basically the firms which are connected

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to the banks are more affected other than the firms which

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are dependent on public debt.

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And this basically shows that how a crisis

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that is happening, completely different set

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of countries can be propagated to international

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or global integration of financial channels due

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to financial globalization,

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overall globalization, et cetera, et cetera, et cetera.

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So this is another set of studies.

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The other study, which is, which is other set of studies,

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which, which, which really starts

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coming out a a lot, especially

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after the financial crisis of 2008.

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There were previous studies, but

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after the financial crisis of 2008, when we saw first time

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after a long period of time,

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we saw significant decline in world trade.

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The world GDP actually went down by about three to 4%.

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The wall trade actually went down more than four times

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of it, like 16 to 17%.

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So, and we started investigating reason why this wall trade

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went down compared to the high, compared to the GDP.

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And we found basically that finance, which was

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the financial sector shock during the 2008,

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was really important for this going down of trade

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because they have the subprime mortgage crisis

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and banks were in liquidity crisis

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and banks could not give money to the,

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to the firms which are connected to

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and firms couldn't treat.

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And when you were trading, when you are doing exports

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and imports, you are in higher need

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of credit rather than any firms we sell domestically

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because your production

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and your, the in revenue comes with a lag.

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So you much need of a higher demand for credit.

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So these are the two, three broad set of studies which kind

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of go into this.

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My study, and,

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and this is my study, obviously contributes to this,

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contributes to this part of the literature,

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but also kind of highlights that yes, banks are important

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for sure, yes, there are global financial channels,

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but see there is different kinds of banks

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and these different kinds of banks react differently

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to different kinds of shocks.

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And that's why the firms which are connect

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to these different kinds of banks

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are affected differentially.

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So my study contributed

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to literature highlighting the bank ownership per se,

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which is typically a feature

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for developing countries in a sense that let's say in Europe

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and the US you will not find much preval of

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pub pri public sector banks.

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This is prevalent much in the developing economies,

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but this is a very important channel, which

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through which we can understand

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how farm can farm can perform,

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especially in the event of a crisis.

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So this is my contribution to the literature highlighting

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how ownership of banks might play a very important role.

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India, as you know, is, is was not within this,

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cowe of the global financial chain

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or financial subprime mortgage assets investment.

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So Indian banks, by default are not allowed

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by the Central Bank of India, not to depo, not

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to invest more than 5%

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of their bank capital on the subprime mortgage assets.

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So by definition, India was outside of this cob web

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of financial integration, which I mean

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of the subprime mortgage assets, which the,

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from which the crisis actually originated in 2008,

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but northwest standing, there was a huge dis,

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outfall of, FYIs, which,

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which is basically institutional investments by investors

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of about 13.3 billion US dollars

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because they were taking out the money to give money

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to the local branches of the US banks under ma,

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mainly to the US banks.

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So there was, even though India was not part

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of this financial crop ware, this huge, outflow

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of capital from the Indian equity market led to some kind

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of liquidity crisis.

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And because of this outflow of capital, what happened was

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India overnight saw a huge depreciation of the rupe,

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Indian rupe versus the dollar.

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The stock exchange index went down significantly.

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There was this call money rate.

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We, the call money rate is basically through the money rate,

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which banks used to, borrow money.

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That went up significantly overnight.

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It went up by more than 20%. And also all this.

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And there was this decline in the outstanding amount

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of certificates issued by bank in terms of ballroom as well.

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And all this, remember all this happened in India,

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even though India is primarily dominated

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by public sector banks, for example, 60% of all the

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Ballwin is done by public sector banks.

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So it's a huge domination of the public sector banks.

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But still, India saw this huge iniquity crisis

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because of this disinvestment

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that happened from the Indian market during the 2008 crisis,

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just to give out, just to kind of take out this amount

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of money to give this, to kind of make out

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for this liquidity crisis that happened in the US

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and partially in the U This is more

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or less in the US that happened,

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the EU crisis came much later, but it simultaneously came.

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But anyway, so this is kind of the setting in India

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that happened, of this equity investment,

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from the equity mar from the equity market.

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Given this context, about,

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the, the, the financial crisis of India and,

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and how the banks,

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are getting differentially impacted in terms

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of public sector banks getting impacted differentially from

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the other studies and private banks

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getting impacted differentially.

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So there was this data set I was looking for,

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it's called the prowess dataset.

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Uh, it's maintained by the Center for Monitoring

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of the Indian economic.

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Um, it's a, it's a private agency which maintains very

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detailed dataset of Indian corporate firms,

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which are listed in the stock,

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major stock exchanges of India.

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And what is the, what are the unique features,

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why this dataset is important in this case?

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Is there, it comes up

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with a few unique features of this dataset.

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Um, one is it gives very detailed information on all the

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credit relationships of all the forms.

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So you know which a form is connected

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to which bank and getting credit from which bank.

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And, and this data set follows that form over time.

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So you then you can understand

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how this banking relationships

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or per se credit relationships of these firms are getting

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changed over time.

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So you have a dynamic specification

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of banking relationships over time.

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So that is one of the unique feature

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because in this case, I would need that feature

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of the dataset to understand

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how firms are switching their banks,

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maybe switching their banks

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because there's a global financial crisis.

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Maybe public sector banks are more resilient to the crisis.

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That's why they might switch the public sector banks,

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for the, from the private sector banks.

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So this part of the datasets very essential.

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The other second part is

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because I'm looking at the exports

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of, of the firms.

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So all the trade of the firms does,

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or the different kinds of production factors

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that the firms employ.

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It's essential to have balance sheet information

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of the firms, how much the firms are exported,

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how much the firms are importing,

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how much they are paying out wages,

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how much the cap the firms employ capital in terms

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of the production process.

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All this information are recorded in this dataset.

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The third part, which is very important, in,

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in the course of my study is

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the detailed balance sheet information of the banks.

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Because it's,

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because I can say that the,

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because the financial crisis, the banks are important

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for the forms, but why,

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why this form banks are getting differentially impacted.

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What is the mechanism of what is the reason

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for which the banks are reacting differently to the shocks

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or what is the reason why banks are supplying less

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money to the firms?

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So detailed balance sheet information of the banks in terms

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of how much the banks are borrowing,

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how much the banks are lending,

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how much the banks are getting deposits.

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All these information are recorded in this dataset.

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So this is, comes from all these three important features

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are, will be utilized in course of the open course

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of the analysis in order to answer the questions

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and in terms of the design of the methodology.

12:50.455 --> 12:53.795
So I employ a very standard, very simple

12:54.365 --> 12:56.275
difference in difference methodology.

12:56.615 --> 12:58.835
So by what I mean by difference, in difference,

12:59.145 --> 13:03.795
what I do is I compare a form which is per se, connected

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to a private bank with a form which is connected

13:08.715 --> 13:10.035
to a public sector bank.

13:10.215 --> 13:14.555
And by comparing these two firms, I compare how much exports

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a form has done in, when a form is connected

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to a public sector bank compared to a private bank.

13:22.355 --> 13:23.435
And this is before and

13:23.435 --> 13:27.115
after the crisis that a form which was connected

13:27.115 --> 13:31.275
to public private bank was doing exports before the crisis

13:31.495 --> 13:34.715
and after the crisis compared to a form which is connected

13:34.715 --> 13:37.155
to a public sector bank before and after the crisis.

13:37.975 --> 13:40.315
So this is a simple difference in difference methodology

13:40.575 --> 13:45.515
to understand why, this is, this is, compared

13:45.575 --> 13:47.755
to two set of firms, what is the effect?

13:47.755 --> 13:50.915
So essentially what I'm trying to say is, is basically

13:50.985 --> 13:53.635
what my analysis say is, is a differential effect

13:54.225 --> 13:55.755
between these two set of firms.

13:56.215 --> 13:58.835
I'm not talking about per se an absolute effect,

13:58.835 --> 14:00.915
but relative effect between these two set of firms.

14:02.415 --> 14:04.715
But as you can imagine, this is

14:05.435 --> 14:07.635
severely problematic in terms of estimating

14:07.635 --> 14:10.155
because banking relationships are,

14:10.535 --> 14:13.235
are endogenous in a sense depends on a lot

14:13.235 --> 14:16.955
of different factors rather than this, this,

14:17.185 --> 14:20.635
this than the forms than any other,

14:20.745 --> 14:22.035
form level characteristics.

14:22.095 --> 14:26.115
So using this, this data set, I can control

14:26.215 --> 14:28.075
for different other characteristics

14:28.385 --> 14:30.195
that can drive this form.

14:30.195 --> 14:31.475
Banking relationships.

14:31.905 --> 14:34.595
Also what I do is I utilize

14:35.305 --> 14:38.195
when a bank is connected to a form

14:38.335 --> 14:42.595
or a form connection to a bank in terms of way in,

14:42.655 --> 14:45.115
in years which are way before the crisis.

14:45.615 --> 14:49.755
So the crisis per se, does not influence the form

14:49.815 --> 14:51.565
to form relationships with the banks.

14:51.985 --> 14:55.565
For example, I use bank form banking relationships

14:55.625 --> 14:59.535
for the years 2000, which is, which is not close

14:59.535 --> 15:01.815
to the crisis in the year 2000.

15:01.875 --> 15:05.655
No one has an idea about the crisis was coming in 2008 so

15:05.655 --> 15:08.975
that the crisis might not affect my bank farm,

15:09.055 --> 15:11.335
bank relationships because as you can imagine,

15:11.835 --> 15:15.215
if the firms would know that getting connected

15:15.215 --> 15:20.055
to public sector banks might affect, might affect me less

15:20.075 --> 15:22.535
during the crisis, they can switch from a private

15:22.565 --> 15:23.775
bank to a public sector bank.

15:24.035 --> 15:26.535
And this might kind of biased my estimates.

15:26.915 --> 15:31.305
So what I do is kind of, I take out of sample estimates

15:31.605 --> 15:34.185
and our banking relationships, which is way

15:34.185 --> 15:37.025
before the crisis to serve as a proxy

15:37.645 --> 15:39.945
for my banking relationships during the crisis.

15:40.125 --> 15:41.465
So this is more

15:41.465 --> 15:44.345
or less the design, the methodology in terms

15:44.365 --> 15:47.185
of the difference in difference methodology, which I use

15:47.415 --> 15:49.505
with a lot of, we

15:49.505 --> 15:52.465
what we call fixed effects methodology in, in,

15:52.595 --> 15:55.825
where we control for several unobservable characteristics

15:57.365 --> 16:00.625
to which can drive this banking form, banking relationships

16:00.885 --> 16:04.225
to estimate, my effect, the relative effect

16:04.225 --> 16:07.185
of the banking ownerships on the farm exports.

16:07.985 --> 16:10.345
I have two set of results more or less.

16:10.755 --> 16:14.665
First I exploit these banking relationships of the farms

16:14.685 --> 16:18.625
to show that the firms which declined to this domestic,

16:18.685 --> 16:20.545
pub, private sector, private banks

16:20.965 --> 16:25.465
and foreign banks, especially of the US origin,

16:25.465 --> 16:29.985
receive less credit about 15% less credit,

16:30.135 --> 16:33.865
than any farm, which is connected

16:33.865 --> 16:35.065
to the public sector banks

16:35.065 --> 16:36.665
because that's the first stage, right?

16:36.735 --> 16:39.225
Because you are getting impacted,

16:39.445 --> 16:41.505
but first you getting less credit,

16:41.505 --> 16:42.905
that's why you're getting impacted.

16:43.605 --> 16:44.945
So that's why I first show

16:45.255 --> 16:47.545
that the firms which are connected to the public sector,

16:47.545 --> 16:50.865
private banks putting together both the domestic private

16:50.925 --> 16:53.945
and the foreign are getting less credit than any other firms

16:53.945 --> 16:55.465
which are connect to the private sector banks.

16:55.485 --> 16:58.545
And the credit is about 15% less credit they're

16:58.545 --> 16:59.785
getting second.

17:00.215 --> 17:03.665
Then I look at how they're getting impacted in terms

17:03.685 --> 17:06.385
of the sales exports and other kind of factors.

17:06.525 --> 17:10.105
So what I find is forms which are connected

17:10.105 --> 17:12.785
to the private banks are getting, are

17:13.495 --> 17:15.825
earning about 50 10%

17:16.415 --> 17:20.025
less from sales than forms which are connected to the

17:20.685 --> 17:21.785
public sector banks.

17:22.085 --> 17:25.705
In terms of exports, the effect is significantly higher.

17:25.845 --> 17:27.185
And as you, as I was saying

17:27.205 --> 17:29.905
before, the farms, which actually exports

17:29.905 --> 17:34.585
of which actually do trade, they are significantly

17:35.135 --> 17:36.665
more in demand for credit

17:36.815 --> 17:38.705
because there are significant lack.

17:38.765 --> 17:42.625
So in terms of exports, the effect went up to 25%.

17:43.365 --> 17:44.985
So firms which are connected,

17:45.075 --> 17:48.825
let's say firms which are connected to public sector, banks

17:49.785 --> 17:54.085
are earning 25% more than the firms which are connected

17:54.085 --> 17:55.125
to the private sector banks.

17:55.585 --> 17:59.045
For example, if a firm which is connected to a private bank,

17:59.065 --> 18:03.125
if are earning pri private bank, which is earning,

18:04.025 --> 18:06.485
75 pounds,

18:07.705 --> 18:10.765
and the form, connected

18:10.765 --> 18:12.805
to public sector bank would be earning hundred pounds.

18:13.905 --> 18:16.685
So that's the difference in terms of,

18:16.685 --> 18:17.685
production factors.

18:18.065 --> 18:21.925
Uh, also I I found that the firms,

18:21.925 --> 18:25.245
which are connected to the public private banks are actually

18:25.265 --> 18:29.485
giving about 5% less, four to 5% less wages,

18:30.065 --> 18:32.005
to to, to the,

18:32.145 --> 18:34.445
to their employees rather than the banks,

18:34.505 --> 18:36.165
rather than the firms which are connected

18:36.165 --> 18:37.285
to the public sector banks

18:38.145 --> 18:42.245
and also importing less, especially the less public goods,

18:42.245 --> 18:44.325
intermediate, intermediate goods.

18:44.945 --> 18:49.245
And these are this negative effect on the firms,

18:49.575 --> 18:50.965
especially,

18:51.685 --> 18:54.805
pronounced when the firms are selling intermediate goods

18:54.825 --> 18:56.245
rather than final goods

18:56.475 --> 19:00.365
because intermediate goods can be stopped in final goods.

19:00.365 --> 19:02.485
You because it's a crisis time, what

19:02.595 --> 19:04.605
what you can need is final goods.

19:04.745 --> 19:08.085
But because the production in stock intermediate Goodson are

19:08.085 --> 19:09.845
stopped because intermediate goods are used

19:09.845 --> 19:11.165
for the production of final goods.

19:11.465 --> 19:14.805
So the effect was pronounced on final goods significantly

19:14.905 --> 19:16.805
higher than any other goods.

19:16.805 --> 19:21.205
And if you go in terms of fine farm sizes, all

19:21.435 --> 19:25.165
farm size across the distribution are

19:25.165 --> 19:26.445
significantly impacted.

19:27.025 --> 19:28.605
So, and,

19:29.225 --> 19:32.685
but there is an interesting effect that that was found out

19:32.915 --> 19:35.685
that the firms which are part of this part

19:35.685 --> 19:39.245
of a business group or a part of a Congo, though,

19:39.305 --> 19:43.645
for those firms, this impact gets mitigated by about 40%.

19:44.225 --> 19:47.885
So that, what that means is when of when you're part

19:47.885 --> 19:50.925
of a business group, there is an internal capital market

19:50.955 --> 19:53.165
that is at work because there are many

19:53.165 --> 19:54.285
firms within the business group.

19:54.305 --> 19:57.485
So you can borrow among each other, when there's a

19:58.105 --> 20:01.605
demand for credit, when when you do not get, credit from

20:01.605 --> 20:04.005
outside sources, you get credit from inside sources.

20:04.465 --> 20:06.765
So that's, this effect gets mitigated

20:06.825 --> 20:11.005
by about a 40% when a form is a part of a business group.

20:11.105 --> 20:12.765
So this is more or less the finding,

20:14.415 --> 20:16.755
from, from the paper.

20:17.485 --> 20:20.595
There are few things that would be interesting

20:20.595 --> 20:23.115
to look at in, in terms of the future research.

20:23.855 --> 20:28.795
One is you were, you can see that the firms

20:29.365 --> 20:30.395
which are connected

20:30.395 --> 20:33.235
to this private banks are getting more impacted.

20:33.455 --> 20:36.235
The firms which are getting connected to the public sector,

20:36.275 --> 20:37.595
banks are getting less impacted.

20:37.695 --> 20:39.115
Now the question comes out

20:39.465 --> 20:42.595
that whether these public sector banks are

20:43.435 --> 20:46.875
shielding the forms which are not supposed to be shipped,

20:47.855 --> 20:50.005
let's say these are inefficient firms

20:50.465 --> 20:53.245
and you are still shielding these inefficient firms,

20:53.355 --> 20:56.885
that means you are actually allocating capital,

20:58.165 --> 21:01.165
locating capital or allocating capital not

21:01.165 --> 21:02.365
in an efficient manner.

21:02.905 --> 21:04.805
So in other sense is that,

21:04.945 --> 21:07.125
are you protecting the zombie firms

21:07.665 --> 21:09.765
in a sense the forums which are supposed

21:09.765 --> 21:12.245
to be die out during a shock?

21:13.065 --> 21:15.165
That's, that's the big question here.

21:15.475 --> 21:17.525
That, and the next question or,

21:17.525 --> 21:20.725
or the conclusion in terms of or the future set of research

21:21.465 --> 21:25.125
or the implication could be that to look at whether

21:25.675 --> 21:27.685
what kind of forms in terms

21:27.685 --> 21:30.325
of the capital allocation are being protected

21:30.345 --> 21:34.005
or being impacted on what kind of forms actually got,

21:34.005 --> 21:38.325
because the, because there was private banks got impacted

21:38.465 --> 21:39.565
and they couldn't give money.

21:39.625 --> 21:42.085
Is it the good forms that got impacted?

21:42.265 --> 21:44.525
Is it the bad firms that not got impacted?

21:44.945 --> 21:49.045
And if that such is the case, then your overall

21:49.615 --> 21:54.565
inequality or overall misallocation problem in an economy in

21:54.565 --> 21:56.805
the macro sense is getting magnified

21:56.805 --> 21:59.205
because you are protecting inefficient firms

21:59.665 --> 22:01.725
and you're not protecting the efficient firms.

22:02.075 --> 22:06.645
Because in the developing countries, what happens is, is

22:06.645 --> 22:08.605
during this crisis times a lot

22:08.605 --> 22:11.565
of expansion policy was being undertaken in order

22:11.625 --> 22:12.885
to protect some of the firms.

22:13.465 --> 22:17.885
And, and this could, might kind of had a long-term impact on

22:18.635 --> 22:20.885
kind of protecting these inefficient forms

22:20.915 --> 22:23.285
because it should not be protecting those farm

22:23.975 --> 22:26.365
which was supposed to get impact getting,

22:27.585 --> 22:29.155
getting the impact

22:29.155 --> 22:31.755
of the shock rather than the forms which should not be

22:31.755 --> 22:32.795
getting impact of the shock.

22:33.175 --> 22:34.675
So this is kind of the f and,

22:34.675 --> 22:39.595
and there was a there was an annual lecture by,

22:39.695 --> 22:43.635
famous economist, KU Raja who, who, who,

22:43.655 --> 22:47.275
who teaches in, in the, in the university of,

22:47.275 --> 22:48.795
Chicago Boot School of Business.

22:49.095 --> 22:52.235
And he spoke in the annual lecture of, bank

22:52.235 --> 22:55.235
of International Settlements in Basel in 2013.

22:55.655 --> 22:58.875
And he really, highlighted this

22:59.585 --> 23:04.315
because this kind of, firms which are coming

23:04.335 --> 23:06.795
to the public sector, banks are getting less impacted.

23:07.005 --> 23:08.675
These evidences are coming out

23:09.055 --> 23:11.875
and he kind of spoke that if the public,

23:11.975 --> 23:15.715
if the public sector banks are protecting those firms which

23:15.715 --> 23:18.395
are not supposed to be protected, then it's kind

23:18.395 --> 23:20.595
of a step in the dark in a sense.

23:20.655 --> 23:24.155
You are increasing your long run misallocation

23:24.155 --> 23:25.275
problem in the economic.

23:25.615 --> 23:28.515
And if you're increasing this long run misallocation problem

23:28.575 --> 23:32.195
in the economic, then the, then the productivity,

23:32.305 --> 23:34.795
overall productivity of the economic goes down

23:35.225 --> 23:39.155
because the farms which are supposed to supposed

23:39.155 --> 23:41.235
to perform well, they are getting impacted.

23:41.855 --> 23:44.515
And you, when you are getting impacted by a shock

23:44.695 --> 23:46.245
And there is a transition phase

23:46.265 --> 23:49.605
or a gestation period to come up to your previous level

23:49.945 --> 23:53.045
and that kind of hampers the overall productivity

23:53.105 --> 23:54.805
of the productivity of the economy.

23:54.865 --> 23:58.645
So yes, so future would be to look at a future set

23:58.645 --> 24:00.645
of research would be to look at which types

24:00.645 --> 24:02.365
of forms cardiac caught impacted

24:02.785 --> 24:06.085
and how it has implications for the overall productivity

24:06.105 --> 24:08.965
of the misallocation and productivity of the economy.

"Bank Ownership and Its Impact on Firm Performance: Insights from Brazil and India Post-2008 Financial Crisis"

00:00:00 - When I was kind of doing a research for this or understanding how banks could matter for foreign performance, two kind of studies caught my attention. One was in Brazil and one was India. And this kind of, caught out after the financial crisis of 2008. They were showing that especially in Brazil, that the regions in Brazil, which have higher proportion of public sector banks, compared to private banks, those regions during the financial crisis had a higher impact or positive impact in terms of employment, local GDP, et cetera. And also on the other side, there are one study which shows
00:00:45 - and the public sector banks are differentially affected during the crisis. So given kind of these two studies, it get me kind of thinking that whether since the banks are differentially affected, what happened to the firms which are kind of a associated to these banks, whether these firms getting credit from these banks could be differentially impacted because the banks themselves are differentially impacted. So these two studies, let me think about whether, or let me get deep about whether firms are getting impacted due to, and whether ownership in this case and actually playing a role help form performance in terms
00:01:26 - sales export, et cetera, et cetera. There are three kinds of literature overall. One in, in very recent, one actually that starts with mental Friedman books in 1969 and, which talks about how banks are very important for, for performance. And they kind of talk about, during the Great Depression of 19 20 19, 19 33, showing that how firms, because how firms, how banks were helping firms in coming out of the depression during, in and especially in the United States during the Great Depression of 1929 to 33. And there were subsequent studies, especially in the recent,
00:02:09 - that banks are very important for foreign performance. Like there is a paper in Japan, for Japan, which came out in quarterly Journal of Economics, which shows that the bank health is very important for form exports. If the bank's health or banks, credit is very good. And the forms connected to those banks perform very good, especially in terms of, in the exports market in the world market. So this is one part of the literature that talks about bank health is very important for foreign performance. And these papers are in the recent era. Why? Because this is for this, you need very micro level of data,
00:02:51 - connected to which of the firms. And in the, in the couple of last couple of tickets we have kind of coming out of micro level data sets where we can really go into these data sets to understand how banks are important for foreign performance. There's this other study set of studies which talks about how financial shocks are propagated to banking channels because of global integration. And there was a study, very interesting study in, published in Journal of Financial Economics, which, which talks about, how forms which were connected to the banks, which were dependent, which were affected due to the crisis, the Russian crisis,
00:03:37 - And they show that basically the firms which are connected to the banks are more affected other than the firms which are dependent on public debt. And this basically shows that how a crisis that is happening, completely different set of countries can be propagated to international or global integration of financial channels due to financial globalization, overall globalization, et cetera, et cetera, et cetera. So this is another set of studies. The other study, which is, which is other set of studies, which, which, which really starts coming out a a lot, especially

"The Impact of the 2008 Financial Crisis on Global Trade and Banking Dynamics: A Focus on Developing Economies"**

00:04:16 - There were previous studies, but after the financial crisis of 2008, when we saw first time after a long period of time, we saw significant decline in world trade. The world GDP actually went down by about three to 4%. The wall trade actually went down more than four times of it, like 16 to 17%. So, and we started investigating reason why this wall trade went down compared to the high, compared to the GDP. And we found basically that finance, which was the financial sector shock during the 2008, was really important for this going down of trade
00:04:57 - and banks were in liquidity crisis and banks could not give money to the, to the firms which are connected to and firms couldn't treat. And when you were trading, when you are doing exports and imports, you are in higher need of credit rather than any firms we sell domestically because your production and your, the in revenue comes with a lag. So you much need of a higher demand for credit. So these are the two, three broad set of studies which kind of go into this. My study, and, and this is my study, obviously contributes to this,
00:05:40 - but also kind of highlights that yes, banks are important for sure, yes, there are global financial channels, but see there is different kinds of banks and these different kinds of banks react differently to different kinds of shocks. And that's why the firms which are connect to these different kinds of banks are affected differentially. So my study contributed to literature highlighting the bank ownership per se, which is typically a feature for developing countries in a sense that let's say in Europe and the US you will not find much preval of pub pri public sector banks. This is prevalent much in the developing economies,
00:06:23 - through which we can understand how farm can farm can perform, especially in the event of a crisis. So this is my contribution to the literature highlighting how ownership of banks might play a very important role. India, as you know, is, is was not within this, cowe of the global financial chain or financial subprime mortgage assets investment. So Indian banks, by default are not allowed by the Central Bank of India, not to depo, not to invest more than 5% of their bank capital on the subprime mortgage assets.
00:07:05 - of financial integration, which I mean of the subprime mortgage assets, which the, from which the crisis actually originated in 2008, but northwest standing, there was a huge dis, outfall of, FYIs, which, which is basically institutional investments by investors of about 13.3 billion US dollars because they were taking out the money to give money to the local branches of the US banks under ma, mainly to the US banks.
00:07:43 - of this financial crop ware, this huge, outflow of capital from the Indian equity market led to some kind of liquidity crisis. And because of this outflow of capital, what happened was India overnight saw a huge depreciation of the rupe, Indian rupe versus the dollar. The stock exchange index went down significantly. There was this call money rate. We, the call money rate is basically through the money rate, which banks used to, borrow money. That went up significantly overnight. It went up by more than 20%. And also all this.

"The Impact of Public Sector Banks on India's Financial Crisis and the Significance of the Prowess Dataset"**

00:08:27 - of certificates issued by bank in terms of ballroom as well. And all this, remember all this happened in India, even though India is primarily dominated by public sector banks, for example, 60% of all the Ballwin is done by public sector banks. So it's a huge domination of the public sector banks. But still, India saw this huge iniquity crisis because of this disinvestment that happened from the Indian market during the 2008 crisis, just to give out, just to kind of take out this amount of money to give this, to kind of make out
00:09:08 - and partially in the U This is more or less in the US that happened, the EU crisis came much later, but it simultaneously came. But anyway, so this is kind of the setting in India that happened, of this equity investment, from the equity mar from the equity market. Given this context, about, the, the, the financial crisis of India and, and how the banks, are getting differentially impacted in terms of public sector banks getting impacted differentially from the other studies and private banks
00:09:48 - So there was this data set I was looking for, it's called the prowess dataset. it's maintained by the Center for Monitoring of the Indian economic. it's a, it's a private agency which maintains very detailed dataset of Indian corporate firms, which are listed in the stock, major stock exchanges of India. And what is the, what are the unique features, why this dataset is important in this case? Is there, it comes up with a few unique features of this dataset. one is it gives very detailed information on all the credit relationships of all the forms. So you know which a form is connected
00:10:31 - And, and this data set follows that form over time. So you then you can understand how this banking relationships or per se credit relationships of these firms are getting changed over time. So you have a dynamic specification of banking relationships over time. So that is one of the unique feature because in this case, I would need that feature of the dataset to understand how firms are switching their banks, maybe switching their banks because there's a global financial crisis. Maybe public sector banks are more resilient to the crisis. That's why they might switch the public sector banks,
00:11:11 - So this part of the datasets very essential. The other second part is because I'm looking at the exports of, of the firms. So all the trade of the firms does, or the different kinds of production factors that the firms employ. It's essential to have balance sheet information of the firms, how much the firms are exported, how much the firms are importing, how much they are paying out wages, how much the cap the firms employ capital in terms of the production process. All this information are recorded in this dataset. The third part, which is very important, in,
00:11:53 - the detailed balance sheet information of the banks. Because it's, because I can say that the, because the financial crisis, the banks are important for the forms, but why, why this form banks are getting differentially impacted. What is the mechanism of what is the reason for which the banks are reacting differently to the shocks or what is the reason why banks are supplying less money to the firms? So detailed balance sheet information of the banks in terms of how much the banks are borrowing, how much the banks are lending,

"Methodological Framework for Analyzing the Impact of Banking Relationships on Firm Performance During Financial Crises"

00:12:33 - All these information are recorded in this dataset. So this is, comes from all these three important features are, will be utilized in course of the open course of the analysis in order to answer the questions and in terms of the design of the methodology. So I employ a very standard, very simple difference in difference methodology. So by what I mean by difference, in difference, what I do is I compare a form which is per se, connected to a private bank with a form which is connected to a public sector bank. And by comparing these two firms, I compare how much exports
00:13:19 - to a public sector bank compared to a private bank. And this is before and after the crisis that a form which was connected to public private bank was doing exports before the crisis and after the crisis compared to a form which is connected to a public sector bank before and after the crisis. So this is a simple difference in difference methodology to understand why, this is, this is, compared to two set of firms, what is the effect? So essentially what I'm trying to say is, is basically what my analysis say is, is a differential effect between these two set of firms.
00:13:58 - but relative effect between these two set of firms. But as you can imagine, this is severely problematic in terms of estimating because banking relationships are, are endogenous in a sense depends on a lot of different factors rather than this, this, this than the forms than any other, form level characteristics. So using this, this data set, I can control for different other characteristics that can drive this form. Banking relationships. Also what I do is I utilize when a bank is connected to a form
00:14:42 - in years which are way before the crisis. So the crisis per se, does not influence the form to form relationships with the banks. For example, I use bank form banking relationships for the years 2000, which is, which is not close to the crisis in the year 2000. No one has an idea about the crisis was coming in 2008 so that the crisis might not affect my bank farm, bank relationships because as you can imagine, if the firms would know that getting connected to public sector banks might affect, might affect me less
00:15:22 - bank to a public sector bank. And this might kind of biased my estimates. So what I do is kind of, I take out of sample estimates and our banking relationships, which is way before the crisis to serve as a proxy for my banking relationships during the crisis. So this is more or less the design, the methodology in terms of the difference in difference methodology, which I use with a lot of, we what we call fixed effects methodology in, in, where we control for several unobservable characteristics to which can drive this banking form, banking relationships
00:16:04 - of the banking ownerships on the farm exports. I have two set of results more or less. First I exploit these banking relationships of the farms to show that the firms which declined to this domestic, pub, private sector, private banks and foreign banks, especially of the US origin, receive less credit about 15% less credit, than any farm, which is connected to the public sector banks because that's the first stage, right? Because you are getting impacted, but first you getting less credit,

"Impact of Bank Ownership on Firm Performance During Financial Crises: A Comparative Analysis of Public and Private Sector Connections"

00:16:43 - So that's why I first show that the firms which are connected to the public sector, private banks putting together both the domestic private and the foreign are getting less credit than any other firms which are connect to the private sector banks. And the credit is about 15% less credit they're getting second. Then I look at how they're getting impacted in terms of the sales exports and other kind of factors. So what I find is forms which are connected to the private banks are getting, are earning about 50 10% less from sales than forms which are connected to the public sector banks.
00:17:25 - And as you, as I was saying before, the farms, which actually exports of which actually do trade, they are significantly more in demand for credit because there are significant lack. So in terms of exports, the effect went up to 25%. So firms which are connected, let's say firms which are connected to public sector, banks are earning 25% more than the firms which are connected to the private sector banks. For example, if a firm which is connected to a private bank, if are earning pri private bank, which is earning,
00:18:07 - and the form, connected to public sector bank would be earning hundred pounds. So that's the difference in terms of, production factors. also I I found that the firms, which are connected to the public private banks are actually giving about 5% less, four to 5% less wages, to to, to the, to their employees rather than the banks, rather than the firms which are connected to the public sector banks and also importing less, especially the less public goods, intermediate, intermediate goods.
00:18:49 - especially, pronounced when the firms are selling intermediate goods rather than final goods because intermediate goods can be stopped in final goods. You because it's a crisis time, what what you can need is final goods. But because the production in stock intermediate Goodson are stopped because intermediate goods are used for the production of final goods. So the effect was pronounced on final goods significantly higher than any other goods. And if you go in terms of fine farm sizes, all farm size across the distribution are
00:19:27 - So, and, but there is an interesting effect that that was found out that the firms which are part of this part of a business group or a part of a Congo, though, for those firms, this impact gets mitigated by about 40%. So that, what that means is when of when you're part of a business group, there is an internal capital market that is at work because there are many firms within the business group. So you can borrow among each other, when there's a demand for credit, when when you do not get, credit from outside sources, you get credit from inside sources. So that's, this effect gets mitigated
00:20:11 - So this is more or less the finding, from, from the paper. There are few things that would be interesting to look at in, in terms of the future research. One is you were, you can see that the firms which are connected to this private banks are getting more impacted. The firms which are getting connected to the public sector, banks are getting less impacted. Now the question comes out that whether these public sector banks are shielding the forms which are not supposed to be shipped,

"Assessing the Impacts of Bank Support on Firm Efficiency and Economic Productivity"

00:20:50 - and you are still shielding these inefficient firms, that means you are actually allocating capital, locating capital or allocating capital not in an efficient manner. So in other sense is that, are you protecting the zombie firms in a sense the forums which are supposed to be die out during a shock? That's, that's the big question here. That, and the next question or, or the conclusion in terms of or the future set of research or the implication could be that to look at whether what kind of forms in terms of the capital allocation are being protected
00:21:34 - because the, because there was private banks got impacted and they couldn't give money. Is it the good forms that got impacted? Is it the bad firms that not got impacted? And if that such is the case, then your overall inequality or overall misallocation problem in an economy in the macro sense is getting magnified because you are protecting inefficient firms and you're not protecting the efficient firms. Because in the developing countries, what happens is, is during this crisis times a lot of expansion policy was being undertaken in order
00:22:13 - And, and this could, might kind of had a long-term impact on kind of protecting these inefficient forms because it should not be protecting those farm which was supposed to get impact getting, getting the impact of the shock rather than the forms which should not be getting impact of the shock. So this is kind of the f and, and there was a there was an annual lecture by, famous economist, KU Raja who, who, who, who teaches in, in the, in the university of, Chicago Boot School of Business. And he spoke in the annual lecture of, bank
00:22:55 - And he really, highlighted this because this kind of, firms which are coming to the public sector, banks are getting less impacted. These evidences are coming out and he kind of spoke that if the public, if the public sector banks are protecting those firms which are not supposed to be protected, then it's kind of a step in the dark in a sense. You are increasing your long run misallocation problem in the economic. And if you're increasing this long run misallocation problem in the economic, then the, then the productivity,
00:24:06 - because the farms which are supposed to supposed to perform well, they are getting impacted. And you, when you are getting impacted by a shock And there is a transition phase or a gestation period to come up to your previous level and that kind of hampers the overall productivity of the productivity of the economy. So yes, so future would be to look at a future set of research would be to look at which types of forms cardiac caught impacted and how it has implications for the overall productivity of the misallocation and productivity of the economy.

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