rafmacalaba/datause-encoder-data huggingface dataset:
funds. Sometimes, DBs – such as KfW in Germany -- receive transfers from the government to fund interest rate subsidies to a particular type of borrower.

Nevertheless, some DBs, like the Vietnam Bank for Social Policies (VBSP), have become highly dependent on government transfers to operate. VBSP prices most of its lending products at interest rates well below market rates. For some of its lending products, interest rates are even lower than the interest rates for its saving products. As a result, it operates with a negative interest rate spread, making it unable to survive without government subsidies. In fact, 18% of the DBs that receive transfers claimed that if transfers were canceled, they would not be able to operate on a sustainable basis.

As government-owned institutions, 64% of all DBs enjoy the support of their governments who explicitly guarantee their debt and other liabilities. Given that 89% of the DBs can borrow from other financial institutions or issue debt, these guarantees allow them to borrow at a relatively lower cost and eventually transfer that lower cost to final borrowers. The provision of guarantees can be regarded as an effective way of funding DBs, provided that the “guaranteed” DBs play a complementary role, that is, they do not compete with the private banks. Otherwise guarantees become a source of unfair competitive advantage.

# **4. Mandates, Business Models and Financial Products**

## **Mandates**

DBs have been established with a wide range of policy or developmental mandates. On the basis of their mandates, DBs can be divided into two groups: (i) institutions with a narrow and specific mandate, which explicitly refers to the sector(s), type of customers or activities that a DB is expected to support, and (ii) institutions with broad mandates that are formulated in general terms without reference to any particular sector or activity. Examples of this type of mandates are _“...to promote the country’s economic development” or the “well-being of citizens”_ .

**Table 5.  Mandates of DBs**

|**DBs by Type of**<br>**Mandate**|**Market niche**|**Percent of DBs in**<br>**the survey**|
|---|---|---|
|**1. Specific**||**53%**|
||Agriculture|_13%_|
||SMEs|_12%_|
||International trade|_9%_|
||Housing|_6%_|
||Infrastructure|_4%_|
||Localgovernments|_3%_|
||Industrial and other|_6%_|
|**2. Broad**||**47%**|
|**Total**||**100%**|

11
# **III. Method**

> We apply the method in Rajan and Zingales (1998) to investigate the link between extemal financial dependence and industrial growth during financial crises. Rajan and Zingales (1998) relate re.al grnwth in va u e **_ndded nf_** a sertnr **tn** an intprqrtinn **ti'rm** that **inrhuiii1** a **pnrnoyv** f **foin2n,,-ial** development and an index of external financiai dependence. Tney snow tiat nrms that are reiatively more dependent on extemal finance develop disproportionally faster in countries with moredeveloped or deeper financial markets, that is, they find a positive relation between the interaction term and real growth in value added.

Their index of extemal dependence is constructed at the industry level based on data of US firrms Thevychonoe the finanrcial structure of US industriesaStheir be-ncimirk because the relatively open, sophisticated, and developed US financial markets shouid allow US firms to face the fewest obstacles to achieving their desired financial structure. This approach offers a valid and exogenous way to identify the extent of extemal dependence of an industry anywhere in the world under the assumption that there are technological and economic reasons why some industries depend more on extemal finance than others, and that these differences persist across countries. They also overcome some of thte identifirqtion prnblem.s emh.edded in standard cross-country growth rperessions by usingg an interaction between a counry cnaractenstic knnanciai aeveiopment of a particuiar country) and an industry characteristic (external financial dependence of a particular industry) in addition to country indicators and industry indicators. This approach allows them to isolate the impact of financial development on industry growth after controlling for cross-country and within-country differences, and is therefore less subject to criticism about an omitted variable bias or model 6
# **Exhibit 2.14 – Investment indicators**

_<u>Medians and means for 2003-07</u>_

||**Net fixed asset**<br>**growth (%)**<br>**Retained**<br>**earnings to**<br>**equity (%)**|
|---|---|
|**Second Tier**||
|Median|-9.4<br>32.6|
|Mean|-3.4<br>34.1|
|**Top Tier**||
|Median|-8.2<br>48.1|
|Mean|-2.2<br>43.1|
|**Peer group (WS)**||
|Median|-3.9<br>17.7|
|Mean|1.2<br>18.4|
|**LMI countries, excl. Egypt (WS)**||
|Median|-8.6<br>19.3|
|Mean|-5.8<br>20.7|

_Source: Coface Egypt;Worldscope; World Bank staff analysis Notes: Retained earnings to Equity from Coface also include Reserves. Whole peer group: Colombia, Chile, Hungary, Indonesia, Israel, Jordan, Mexico, Morocco, Pakistan, Philippines, and Turkey. LMI countries: Colombia, Indonesia, Jordan, Morocco, and Philippines._ Regarding differences between industries, Exhibit 2.15 clearly shows that all tiers and industries have significant negative asset growth, with the exception of Top Tier Travel and Leisure companies, which has been growing rapidly as we found earlier. Exhibit 2.15 also shows that tiers in all sectors have been enjoying strong retained earnings growth, with Top Tiers having superior earning levels, up to more than 20 pp in the Construction and Materials and Industrial Cyclical sectors. Again, Top Tier Travel and Leisure shows strong growth with a CAGR of 49.3 percent.

# **Exhibit 2.15 – Investment analysis by industry**

|_Medians by year and average median and compounded average growth rate of period 2003-2007_|
|---|

||**Travel a**<br>|**nd leisure, m**<br>|**edians**<br>||**Constru**<br>|**ction and ma**<br>|**terials, medi**<br>|**ans**<br>|
|---|---|---|---|---|---|---|---|---|
||**2003**|**2007**|**Average**|**CAGR**|**2003**|**2007**|**Average**|**CAGR**|
|**Yearly net fixed asset growth, %**|||||||||
|Egypt - Second tier (Coface)|NA|-9.6|-9.2|NA|NA|-7.0|-8.8|NA|
|Egypt - Top tier (Coface)|NA|17.4|14.9|NA|NA|-10.5|-10.6|NA|
|**Retained earnings to Equity, %**|||||||||
|Egypt - Second tier (Coface)|18.3|31.2|28.0|11.2|42.3|46.0|38.4|1.7|
|Egypt-Top tier (Coface)|6.6|49.3|37.8|49.3|59.8|70.7|59.5|3.4|
||**Consum**<br>|**er staples, m**<br>|**edians**<br>||**Industri**<br>|**al cyclical, m**<br>|**edians**<br>||
||**2003**|**2007**|**Average**|**CAGR**|**2003**|**2007**|**Average**|**CAGR**|
|**Yearly net fixed asset growth, %**|||||||||
|Egypt - Second tier (Coface)|NA|-9.7|-9.0|NA|NA|-10.8|-10.4|NA|
|Egypt - Top tier (Coface)|NA|-3.7|-4.9|NA|NA|-8.6|-10.8|NA|
|**Retained earnings to Equity, %**|||||||||
|Egypt - Second tier (Coface)|31.1|34.4|32.9|2.1|26.4|36.3|31.6|6.5|
|Egypt-Top tier (Coface)|37.1|50.9|41.0|6.5|37.1|63.7|50.4|11.4|

_Source: Coface Egypt; World Bank staff analysis_ The fixed asset growth difference between tiers discussed earlier is 1.1 pp higher, even after taking into account sector characteristics, as Exhibit 2.16 shows. However, this difference is not statistically significant and decreases even further to a gap of 0.2 pp once the company size has been accounted for. The retained earnings gap however is real with 15.7 pp and cannot be 14
than theeconoiy that relies on sectoral taxation.

# **hn&-21 gL** ovrMMent **Exveditures**

In describing the effects of taxation we assumed that government expenditures enter separately in the utility function. Relaxing the separability assumption Implicit In (11) can have important Implications for the aetermination of optimal tax and expenditure policies but Is not necessarily relevant for the relation between taxes and growth. To see this suppose that we replace the momentary utility u(Ct) + O(Gt) by a non-separable function v(CttGt). To be consistent with steady state growth this function must have the form: where e(i-@) < I and **<** (i-o) _o_ to ensure strict concavity.

Suppose that the government follows a balanced budget policy by choosing a combination of income tax rate r and government expenditures such that Gt = T AZt. In this case the rate of growth of this economy is, Ignoring the corner solution with zero Investment: If the government does not maintain a constant share of government expenditures 1A Income this economy will not follow a steady state path. In this case the effects of taxation are harder to characterize but the property that higher taxes imply lower growth is generally preserved.

## Evidence for developing countries suggests that certain

8The optimal path for government expenditure, abetractlng from the presence of distorting taxes, Is such that Ct/Gt _G._ 11
performance of the economy. Secondly, the ability of domestic producers to adjust rapidly to demand is itself a factor of competitiveness.

Another, possibly more important aspect is the possibility of dealing correctly with stocks and flows<sup>9</sup> . This is particularly relevant in this context where the correct treatment of the stock of knowledge appears to be important for satisfactory empirical resultsl°.

Let us now discuss the specific equations (see table 1). All equations are expressed as adjustment equations where each endogenous variable X adjusts with a coefficient a , to its partial equilibrium value X*, also the disturbance terms are omitted. As mentioned above the size of adjustment speeds is also an indicator of sectoral competitiveness as it is determined, inter alia, by the "capacity to deliver", hence higher values of a signal higher competitiveness. Eq (1) states that the export share of traditional goods _SA_ adjusts to its partial equilibrium value _S4*_ which varies inversely with the real effective exchange rate P, i.e. we assume that relative technology does not directly affect international competitiveness in this 1ectl2 . Eqs. (2)-(4) . describe the ad2ustment of the export market share in sector' . Eqs. (2)-4.decieteajsmnofteeprmrkthren the three other sectors to their respective partial equilibrium values. Following Pavitt's taxonomy we assume that partial equilibrium values of the export shares for the scale intensive (B) and specialized suppliers (C) sectors are function of both the real effective exchange rate and of the relative stock of knowledge _T/TW,_ while the science based sector's share _(D)_ is function of relative knowledge alone.'<sup>3</sup> A priori, sectoral price and relative knowledge elasticities are assumed to be different. Empirical estimation results (see para. 4) show that this is not always the case, nevertheless significant country differences are present.

9Again the reader is referred to Gandolfo (1981).

> 10 As shown in Verspagen (1993) the use of knowledge indicators such as patents often leads to unsatisfactory empirical results. Maquier and Toujas Bernate (1994) and Amable and Verspagen (1995) obtain much better results apparently because of their more satisfactory treatment of the variables representing the stock of knowledge. Their treatment, nevertheless, is not fully consistent with a correct of stock and flows specification in continuous time.

- 11 In continuous time the reciprocal of the speed of adjustment l/a is the mean time lag. i.e. the time necessary for about 63% of the discrepancy between the actual and the partial equilibrium value to be eliminated. See Gandolfo (1981)

- 12 This is consistent with results obtained by Verspagen (1993) and by Amable and Verspagen (1995) and also by our early attempts to relate the behaviour of _SA_ to the relative stock of knowledge, see below.

- 3 Both Verspagen (1993) and Amable and Verspagen (1995) find empirical support to this assumption.

9
# **Table 13 – Global banks: Adverse reform spillovers affecting participation of branches and subsidiaries in local markets of EMDEs**

_Please indicate the regulatory reforms which contributed to a significant reduction or tightening of your institution’s activities in emerging markets and developing economies (EMDEs), particularly those that are jurisdictions not required to implement the reforms (you can select more than one reform area)._

|**N = 4**|**Risk-based**<br>**capital**<br>**reforms**|**Leverage**<br>**ratio**|**Liquidity**<br>**measures**|**Measures**<br>**dealing with**<br>**systemically**<br>**important**<br>**banks**|**Measures**<br>**dealing with**<br>**OTC**<br>**derivatives**|**Any other**<br>**G20**<br>**financial**<br>**reform**|**No**<br>**Significant**<br>**Impact of**<br>**any reform**|**Don't know**|
|---|---|---|---|---|---|---|---|---|
|Sovereign debt markets|2|1|1|1|0|1|1|0|
|Corporate debt markets|2|0|0|0|0|1|2|0|
|Equitymarkets|1|0|0|0|0|0|3|0|
|Moneymarkets|1|0|0|0|0|0|2|1|
|Foreign currencymarkets|1|0|1|0|2|1|1|0|
|Retail fundingmarkets|1|0|1|0|0|0|2|0|
|Wholesale fundingmarkets|3|1|2|0|0|0|1|0|

35
# **1. Introduction**

To reduce asymmetric information problems associated with extending credit and increase the chances of loan repayment, banks typically require collateral from their borrowers.<sup>1</sup> For example, according to World Bank Enterprise Surveys performed in over 100 countries, collateral was required in over 75% of all loans.<sup>2</sup> Many theoretical models postulate that the availability of collateral is a binding constraint on financing, and that this constraint binds harder in more underdeveloped financial markets (Liberti and Mian, 2010). Empirically, insufficient collateral is one of the main reasons firms are rejected when they apply for bank credit (Fleisig et al., 2006).

Movable assets, as opposed to fixed assets such as land or buildings, often account for most of the capital stock of private firms and comprise an especially large share for micro, small and medium-size enterprises. For example, in the developing world 78% of the capital stock of businesses is typically in movable assets such as machinery, equipment or receivables, and only 22% is in immovable property (see Alvarez de la Campa, 2011). Hence, movable assets are the main type of collateral that firms, especially those in developing countries, can pledge to obtain bank financing. However, banks in developing countries are usually reluctant to accept movable assets as collateral due to the inadequate legal and regulatory environment in which banks and firms co-exist. In this context, movable assets become “dead capital” (Fleisig et al, 2006).<sup>3</sup> While a sound legal and regulatory framework is essential to allow movable assets to be used as collateral, registries for movable assets fulfill two key functions: to notify parties about the existence of a security interest in movable property (of existing liens) and to establish the

> 1 See Steijvers and Voordeckers (2009) for a recent survey of empirical studies on the use of collateral to mitigate credit rationing.

> 2 Enterprise surveys are available at http://www.enterprisesurveys.org/

> 3 For example, Safavian at al. (2006) claim that nearly 90 percent of movable property that could serve as collateral for a loan in the United States would likely be unacceptable to a lender in Nigeria.

2
we use the ES weights throughout this paper, including in the matching method and descriptive statistics.<sup>7</sup>

# **4.2. Dependent Variables**

We focus on four outcome variables measured in COV-ES. These are, (i) the percentage change of permanent full-time workers since December 2019, (ii) whether the firm decreased its total number of temporary workers since the onset of the pandemic, (iii) whether the firm decreased its total hours of operation since the onset of the pandemic, and finally (iv) whether the firm anticipated falling in arrears on outstanding liabilities within the next six months of the date of the COV-ES interview.

Percentage change of permanent full-time workers is calculated using two separate questions of COV-ES. Each respondent is asked to provide the total number of their permanent full-time workers at the end of December 2019. This question was included in the first round of the survey in El Salvador but only implemented in the second round in Georgia. Each respondent is also asked to provide the total number of their permanent full-time workers at the end of the last completed month as of the interview date.

The second and third outcome variables of our interest, i.e., on temporary workers and on total hours of operations, are based on the respective questions included in COV-ES, asking respondents to report whether the respective item increased, remained the same, or decreased. Notably, for the question on temporary workers, the reference period in the first round of the survey is the onset of the pandemic, and in the second round – the previous round. In the question about the total hours of operations, the respondents are asked to compare the last completed month at the time of the interview with the same month one year prior. We create dummy variables taking the value of 1 for firms that report a decrease in the respective question and 0 otherwise. The fourth outcome variable of our interest, i.e., anticipation on arrears, is measured through a Yes/No question included in COV-ES.

Table 3 provides summary statistics of the four outcome variables separately by country and round of COV-ES. Firms in both countries, on average, mostly show statistically significant

> 7 Our results from matching estimation are similar when we use COV-ES weights instead.

12
80% in 2012 (based on data from the ECVH _(Enquete sur les Conditions de Vie en Haiti)_ 2001; DHS 2005; DHS 2012; ECVMAS 2012).<sup>11</sup>

# **<u>Figure 2</u>**

<!-- Start of picture text --> Total number of students (grades 1-6) in treatment and control schools<br>(2002-3 and 2011-12)<br>350<br>294<br>300 277<br>252 254<br>238<br>250 224<br>200 181 211 192 195 174 183 202 185 192 198 179<br>162 154<br>150 120<br>100<br>50<br>0<br>Treatment Control Treatment Control Treatment Control Treatment Control Treatment Control<br> Nord Nord Est Centre Grand Anse Nord Ouest<br>2003 2012<br><!-- End of picture text --> Source: World Bank staff estimates based on 2002-3 and 2011-12 Haiti school census.

Encouragingly, the percentage of primary students 2 or more years over age for their grade fell by 10 percentage points in the treatment group. This seems to be driven in part by lower repetition rates across grades, and these effects are similar for boys and girls. These impacts may be directly caused by the fact that the program only funds students within 2 years of the prescribed age for grade. However, given that effects are also seen in grades 5 and 6, not yet funded by the program, it is possible that participation affects repetition rates through other channels. For example, families may be better able to finance the education of older siblings when younger siblings are covered by the program, allowing them to stay in school more consistently and not have to repeat grades.

Finally, given the large increases in student numbers, the student-teacher ratio increased by 8 on average; the average ratios remain under 40 in treatment schools across four of the five departments, well below the limit of 45 students per class mandated by the program (Figure 3). This increase in ratios may be a cause for concern, as the results of well-identified research, using natural experiments or randomization, suggest that class size differences of this

> 11 The 2001 ECVH measured net primary enrollment at 60%; the 2005 DHS at 50%; the 2012 DHS at 77%; and the 2012 ECVMAS at 72% (IHSI 2003; Cayemittes et al 2007; Cayemittes et al 2012; World Bank 2014). Differences in these measures are due to both the fact that they are sample surveys and that each was conducted in different months and years.

13
- 28 -

shared is fixed even though the shares of individual jurisdictions may vary. Non-matching because the amount received by any jurisdiction is set independently, unrelated to its revenues or expenditures. That is, the requirement that jurisdictions spend the same proportion of their income on education and health as in 1972 has never really been enfotced and while jurisdictions are expected to contribute to educatior. and health expenditures there is no formula relating these to the size of the transfer received from the national government. As constituted, the sharing formula does not further resource allocation or income distribution objectives in any systematic fashion. If the objective were to encourage increased resources in education and health, the appropriate formula would be conditional, open-ended and matching. On the other hand, if the objective were to reallocate resources to poorer jurisdictions or jurisdictions with lower tax bases, the formula should be unconditional not conditional. Moreover, as was shown above, the formula favors jurisdictions with smaller populations in a rather capricious fashion unrelated in any systematic way to needs or to poverty. Lastly, it is clear that the formula does not encourage greater tax effort on the part of departments and available evidence suggests that tax effort has been reduced. For exa'mple, a 1978 study by the Foundation for Higher Education and Development (FEDESARROLLO) found that the non-matching nature of the formula would in general tend to discourage local effort and that the tax allowance has had no effect on the level of department expenditures in education and health.1<sup>7</sup> A study done by Slack and Bird, as part of their background work for the 1981 Mission on

> 17/ Fundaci6n Para la Educaci6n Superior y el Desarrollo "El Efecto del Situado Fiscal y la Cesion del Impoventas Sobre los Ingresos y la Estructura del Gasto Departmental y Municipal" (unpublished, Bogota, October 1978).