rafmacalaba/datause-encoder-data huggingface dataset:
**Table 2.  Real Fixed Investment Growth ...**

**Figure 10. ... is stagnant (2002-06)**

||**1980**<br>**-89**|**1990**<br>**-96**|**1997**<br>**-01**|**2002**<br>**-05**|**Real Fixed Investment**<br>**(Level. SA. 2000-01=1)**<br>1.8|
|---|---|---|---|---|---|
|China|8.2|15.2|9.9|12.0|Trend Growth 2002 Q1 - 2006 Q4<br>Investment<br>GDP|
|South East Asia|||||1.6<br>Indonesia 8.2% 5.2%<br>Malaysia 4.6% 6.2%|
|Indonesia|8.9|11.5|-5.9|7.2|<br>**Philippines -0.2% 6.0%**<br>|
|Malaysia|7.0|17.7|-6.6|2.2|1.4<br>Malasia<br>Thailand 10.3% 5.7%|
|**Philippines**|**0.4**|**5.3**|**0.2**|**1.1**|y<br>Thailand<br>|
|Thailand<br>NIEs<br>Chinese Taipei|8.5<br>7.4|12.3<br>9.2|-14.5<br>1.7|8.6<br>3.1|1.0<br>1.2<br>Philippines<br>Indonesia|
|Hong Kong, China|5.3|9.3|-0.2|0.7||
|Korea|8.6|11.5|-1.8|2.9|0.8|
|Singapore<br>_Source:_ World Bank,<br>~~h~~|6.3<br>2006a. C|13.1<br>ompoun|0.6<br>d annual|-1.5|Q1-2002<br>Q3-2002<br>Q1-2003<br>Q3-2003<br>Q1-2004<br>Q3-2004<br>Q1-2005<br>Q3-2005<br>Q1-2006<br>Q3-2006|

**Can the investment slowdown be structural?** Potential causes of the investment slowdown are cyclical factors such as the pre-1997 investment boom, the impact of the financial crisis, and the 2001 global high tech recession. But policy makers are concerned that weak investment may reflect not only cyclical but also deep-seated factors, signaling more permanent or long term difficulties in achieving higher growth (Table 2 and Table 3).<sup>15</sup> Indeed, the corporate _élite_ - comfortably protected by political ties - finds convenient investing only a portion of its revenues in-country, and keeps sending considerable portions offshore.

**Table 3. Fixed Investment (as % of GDP)- Pre and Post Crisis Periods**

||**Indonesia**|**Korea**|**Malaysia**|**Philippines**|**Thailand**|
|---|---|---|---|---|---|
|Peak|29.6|37.5|43.6|**24.4**|41.1|
||(1996)|(1996)|(1995)|**(1997)**|(1995)|
|Bottom|19.4|28.0|20.0|**14.6**|20.8|
||(2002)|(2006)|(2005)|**(2006)**|(1999)|
|Latest in 2006*|21.5|28.0|20.4|**14.6**|29.6|
|Bottom – Peak (extent of decline)|-10.2|-9.5|-23.6|**-9.8**|-20.2|
|Latest – Bottom (extent of recovery)|2.0|0.0|0.4|**0.0**|8.7|
|Latest – Peak|-8.2|-9.5|-23.2|**-9.8**|-11.5|

_Source:_ World Bank, 2006a. */ until the second or third quarter depending on data availability.

15 Indeed, in the 1980s (1980-89) investment spending grew at 0.4 percent. In the first part of the 1990s (1990-96) growth rose at 5.3 percent, but between 1997-2001, investment growth was again stagnant at 0.2 percent. In 2001-05, despite the economic recovery, fixed investment picked up modestly (investment growth averaged only around 1 percent).

13
# **I. Introduction**

What started as a crisis in the sub-prime mortgage market in the United States in late 2007 quickly became a full-fledged global financial crisis. The financial crisis led to a massive worldwide economic slowdown, with gross worldwide product shrinking by 2.1 percent in 2009.<sup>2</sup> Although all regions were affected, Eastern Europe and Central Asia (ECA) was hit harder than most. After growing at an annual rate of 7.1 percent in 2007 and 4.2 percent in 2008, GDP in the region contracted by 5.3 percent in 2009—a larger contraction than in any other region (World Bank, 2010). This was accompanied by a large drop in private inflows of capital. In 2007, $491 billion (16 percent of GDP) of private capital came into the region. By 2009, this had fallen to $84 billion. The combination of a drop in demand and a drop in the availability of external financing affected firms throughout the region.

This paper uses two sources of data to assess how the crisis affected different firms in the ECA region. The first, a panel of firms that were interviewed in 2002, 2005, and 2008-9 as part of the Business Environment and Enterprise Performance Surveys (BEEPS), allows us to document how financial constraints evolved over time and to see how firm and country characteristics affected these constraints during the crisis. The second dataset, from the Financial Crisis Surveys (FCS) that were conducted as follow-ups to the BEEPS in six countries in 2009, allows us to look at how changes in access to financing affected firm survival rates during the crisis.

Other papers have used BEEPS data to study access to and use of financial services within the ECA region (Brown et al., 2011; Ongena and Popov, 2010; and Popov and Udell, 2010). Brown et al. (2011), which is the most similar to our analysis, uses data from the 2005 and 2008 BEEPS to compare application for and use of credit in Eastern and Western Europe. Like us, they find that credit constraints softened in Eastern Europe prior to the crisis, but they also find that loan application rates were lower and rejection rates higher in Eastern than Western Europe and that this was associated with the presence of foreign banks. We use data from the 2002, 2005, and 2008 BEEPS, which enables us to better capture both the easing and tightening

> 2 Data in this paragraph are from World Bank (2010).

2
**Table 4. Average Time Period to Remit Money to Sri Lanka (2005)**

|Country|TelegraphicTransfer|Draft/ Cheque|E-Remittance|
|---|---|---|---|
|United Arab Emirates|1-2 Days|3*-21 Days|10-15 Minutes|
|United States|1-2 Days|3*-21 Days|10-15 Minutes|
|European Union|1-2 Days|3*-21 Days|10-15 Minutes|

*On local clearing _Source: Central Bank of Sri Lanka (2005)_

Sri Lanka Post has struck an agreement with the United Emirates Posts, to exchange postal money orders electronically. The Emirates Post will help Sri Lanka Post with the installation of necessary software and training. This appears as a useful first step to improve the level of service with one of the key markets from where remittances originate. In 2004, Sri Lanka Post launched a tender for an agency for urgent money transfers and it was approached by representatives of firms such as MoneyGram and Western Union. A decision on the matter is in process.

# **Informal Remittance Systems**

As is the case in most South Asian countries, informal remittances are commonplace, having long been used to facilitate trade between distant regions where conventional banking instruments are either absent or weak. World Bank (2005a) estimates that unrecorded remittances are highly volatile and could have reached as much as 45 percent of total private remittances in Sri Lanka in the mid-1990s (Figure 4). Broadly speaking, the growth of informal funds transfer systems has traditionally been negatively correlated with the level of development and liberalization of the formal financial sector. Informal systems are more likely to be found in jurisdictions where the formal financial sector is either virtually absent or not functioning—as is sometimes the case in internal regions in conflict—or does not provide a reliable, cost effective, and convenient mechanism for the transfer of funds. The attraction of informal operators is heightened by financial policies that include foreignexchange controls as was the case in Sri Lanka. Over time, the operational features of speed, low cost, ethnic and cultural convenience, versatility, and anonymity led to their use for various legal and illegitimate purposes.<sup>13</sup> Many Sri Lankan banks identify informal remittances as their most challenging competitor. Although some banks have tried to tap into the informal markets, there are no examples of successful models.

9
**Figure 3: Two Indexed Inputs to Regulatory Environment**

<!-- Start of picture text --> Sub Saharan Africa<br>South Asia<br>OECD<br>Corruption<br>MENA<br>global Transparency<br>LAC average<br>ECA<br>East Asia<br>0 0.2 0.4 0.6 0.8 1<br><!-- End of picture text --> Source: Authors’ calculation based on Kaufmann, Kraay and Zoido-Lobaton (2002) and World Competitiveness Yearbook 2002.

**Figure 4: Two Indexed inputs to Service-Sector Infrastructure**

<!-- Start of picture text --> South Asia<br>OECD<br>Middle East Effect of internet on business<br>(higher is huge effect)<br>Latin America and Caribbean<br>Speed & cost of internet access<br>global<br>Europe and Central Asia average (higher is faster and cheaper)<br>East Asia<br>Africa<br>0.000 0.200 0.400 0.60 0 0 .800 1.000<br><!-- End of picture text --> Source: Authors’ calculation based on Global Competitiveness Report 2001-2002.

30
non-owners), and no effect of marginal tax rates on the use of inside debt (loans from owners). Notably, this evidence comes exclusively from publicly listed U.S. firms. As with many aspects of firm financing, bankruptcy costs and asymmetric information in financing decisions of firms in transition and developing countries remain unclear (Prasad et al., 2005).

Using data on Croatian firms, this paper contributes to the literature by demonstrating that − in line with the trade-off theory of debt − firms increased their equity levels as a result of a corporate tax reform. In 2001, Croatia drastically cut its corporate tax rate from 35% to 20%, primarily to promote private sector growth and attract foreign investment [Note: The _General Tax Law (NN No. 127/00)_ , that contained the _Law on Corporate Profit Tax_ , was voted in December 2000 and took effect in January 1, 2001]. This exogenous change in the statutory tax rate was immediately translated into a lower effective tax rate (i.e., taxes divided by pre-tax income). Using the sample of Croatian firms in this study, Figures 1 and 2 illustrate how the mean and median effective tax rate dropped substantially, while the ratio of ‘Equity-to-Assets’ increased, after the corporate tax reform. These changes provide an intuitive indication of a possible relation that ought to be tested further controlling for firm characteristics in order to account for firm-specific factors influencing the choice of capital structure.

[Figures 1 and 2 about here] The remainder of the paper is structured as follows. Section II outlines the motivation for this study, while Section III describes the sample design and estimation methodology. Section IV presents the findings and Section V concludes.

# **II. MOTIVATION**

There are several reasons why the Croatian corporate tax reform offers a unique natural experiment on the impact of corporate taxes on firms’ capital structure choice due to decreased interest tax deductibility: _First_ , cases of substantial corporate tax changes without concurrent changes in personal taxation are unusual, and economic research has traditionally dealt with minor changes in corporate tax policy that yielded mixed findings (Auerbach, 2002). In the United States, the Tax Reform Act of 1986 had mixed results because the maximum statutory tax rate decreased from 46% in 1986 to 34% after 1988, but simultaneous changes in several tax rules raised the fraction 2
<!-- Start of picture text --> log(DPR) log(land value per acre)<br>-2 -1.5 -1 -.5 0 .5 1 1.5 2 -2 -1.5 -1 -.5 0 .5 1 1.5 2<br>-2 -1.5 -1 -.5 0 .5 1 1.5 2 -2 -1.5 -1 -.5 0 .5 1 1.5 2<br>log log<br>.6<br>.8<br>.6 .4<br>.4<br>.2<br>.2<br>0<br>0<br>Marginal effect head channel<br>-.2<br>-.2<br>.05<br>.05<br>.04<br>.04<br>Fraction .03 .03<br>.02 .02<br>.01 .01<br>0 0<br>θ θ<br><!-- End of picture text --> Figure 7: Marginal effects of head outlet by log _θ_ _Notes:_ Left and right upper panels show marginal effects of head outlet at different values of relative lobbying power (log _θ_ ) on, respectively, log(DPR) and log(land value). The former marginal effects are based on column 4 of Table 3 and the latter on column 8 of Table 4. Lower panels show histograms of log _θ_ for the corresponding specifications. Bars in upper panels denote 95% confidence intervals. Short-dashed vertical lines denote one standard deviation above and below the mean of log _θ_ (long-dashed vertical line).

33
other aspects related to the quality of care, including the duration of consultations, whether providers explained the different elements, and whether they encouraged the women to ask questions. However, the presence of observers during the consultations might lead to providers performing better than usual due to observer or Hawthorne effects (Leonard and Masatu 2010). Observer or Hawthorne effects could induce attenuation bias in the estimated socioeconomic gradients if increased provider efforts were more concentrated among poor women. If this was the case, the direct observation results would be a lower bound for the true wealth‐quality gradient and its correlates.

To facilitate comparability, we restrict our analysis of the direct observation and exit interview data to women who were receiving the first consultation of their pregnancy. These consultations are more comparable to each other, because their content does not depend on previous consultations and include procedures that should be conducted regardless of women’s medical and fertility histories. As poorer women attend fewer consultations during their pregnancies, there is also most variation in wealth among women attending a first consultation.

Table C.1, in appendix C, presents the basic sample characteristics. The first panel provides the characteristics of women in the household survey. We restricted the analysis to women who had a live birth in the two years preceding the survey. Because most of the analysis is of the information on content of care, the table is further restricted to the 82 percent of the women who attended at least one antenatal consultation during their recent pregnancy. The second panel presents the characteristics of the sample of pregnant women who completed exit interviews after receiving the first antenatal consultation of their pregnancy. The two samples are overall similar, although women in the household sample are slightly older on average and slightly less likely to have attended secondary school.

Following the methodology originally proposed by Filmer and Pritchett (2001), we use principal component analysis to create a wealth index, using a list of 32 household assets collected in the household survey and exit interviews. For the household sample, the index uses the first principal component of the entire sample of households regardless of whether the pregnancy was completed or the woman had attended any antenatal consultation. We normalize the index to mean zero and a standard deviation of one to facilitate the interpretation of the estimated coefficients. For the exit interview sample, the wealth index was constructed with the assets reported in the exit interviews applying the factor scores computed with the household data to ensure direct comparability of the scores. The average wealth in the exit interviews is higher by 0.75 standard deviation than the average wealth in the household data.

7
manufacturing and installation stage (less so in operation and maintenance, partly because fuel input management is not necessary).

Fankhauser et al. (2008) note two important caveats. First, higher labor intensity per unit of energy capacity created implies lower labor productivity than in conventional energy production. Renewable energy may be more expensive and less efficient than conventional sources, with high capital as well as labor requirements, shorter-lived plant and more intermittent energy production. Thus some studies of potential employment creation ignore the question of whether it would be profitable for the private sector to adopt the programs considered. Second, labor is relatively immobile in the short run, so policy changes may create transitional frictional unemployment due to the structural change induced. Both points reflect the tendency for employment creation studies to be vague about the macroeconomic adjustment mechanisms implicit in their estimates.

In addition to those two caveats, studies rarely take into account the macroeconomic consequences of higher real energy prices (or higher energy subsidies) on the overall price level, labor supply, labor productivity and taxation. Converting countries’ energy sectors to low-carbon technologies is likely to require increased investment. McKinsey & Company (2009) estimates that the annual incremental investment costs required to get the global economy on to an appropriate low-carbon trajectory would be EUR 320 billion by 2015. The IEA (IEA, 2008) and UNFCCC (UNFCCC, 2007) suggest a similar figure for the incremental costs of power generation in strong climate-change mitigation scenarios. However, the pace of the transformation may be constrained by the cost and/or availability of financial capital (given the risk characteristics of the investments involved) or incur a higher cost in terms of investment and employment displaced elsewhere in the economy.

A further caveat is that studies tend to focus on alternative energy supply scenarios rather than considering a broader range of alternatives, some of which could entail greater job creation still. For temporary counter-cyclical employment creation, higher spending in sectors with lower capital intensities than either conventional or renewable energy – such as education and health services – may be more effective (although perhaps more difficult to unwind when macroeconomic circumstances improve).

15
6 While this paper relates directly to a small literature on the policies and institutions underpinning sustainable financial development, it also relates to a much larger literature on the relationship between financial deepening and economic development. While extensive empirical work has shown a positive relationship between financial depth and economic growth (see Levine, 2005, for an overview), recent work has pointed to important non-linearities in this relationship or even a range of financial depth where this relationship turns negative (Aghion et al., 2005; Arcand et al., 2012). This is in addition to an extensive literature that has shown that rapid increases in credit are associated with a higher likelihood of systemic banking distress (Demirguc-Kunt and Detragiache, 2005).<sup>3</sup> The remainder of this paper is structured as follows. The next section introduces the concept of the financial possibility frontier. Section 3 uses the concept to discuss different policy options for sustainable financial deepening. Section 4 introduces the benchmarking exercise and section 5 uses the example of the transition economies to illustrate its application. Section 6 discusses the access possibilities frontier for SMEs and the use of Enterprise Surveys. Section 7 uses the example of Egypt to demonstrate the need to use both aggregate and micro data. Section 8 concludes.

# **2. The financial possibility frontier**

The section introduces the financial possibility frontier, a concept that builds on previous work by Beck and de la Torre (2007) and Barajas et al. (2012).

> 3 For a discussion on how banking fragility has affected households in Eastern Europe, see Brown (2013).
roads in the range of 25 to 35 miles per hour, grades in the range of 7 to 12 percent may be appropriate (Wolshon, 2004). In terms of construction cost, a higher grade means a shorter road, requiring less earth and drainage work and hauling. Given the limit on maximum grade, the optimal route in an area with steep slopes requires longer roads to reach a given elevation as curves are added to ensure gentler grades. Very steep slope may also require cuts and ...lls which add substantially to road construction costs. Slope of an area thus a¤ects placement and design of roads, providing an exogenous source of variation in the travel time. One can thus plausibly use a measure of DSD level slope as an instrument for travel time. To make the exclusion restriction as clean as possible, instead of own slope of a DSD, we use the deviation of own slope from the average slope of other DSDs in the district as an instrument for travel time. Identi...cation of the e¤ect of travel time is thus based on the variations in travel time that arises solely from exogeneous variations created by di¤erences in the slopes. One might argue that we need to control for the own slope of a DSD so that the di¤erence in slope cannot pick up any potential direct e¤ect of the slope of a DSD on labor market equilibrium. On a priori grounds, this would make the exclusion restriction imposed on the di¤erence of slopes more credible. However, perhaps somewhat surprisingly, the empirical results later show that adding own slope as a conditioning variable actually a¤ects the Hansen’s J statistics adversely, and it has no explanatory power in the wage regressions. So we report results both with and without ‘own slope’as a control variable in the IV regressions. Following the literature, the interaction of travel time and incidence of LDO restrictions is instrumented by interaction of the instrument for travel time with one of the instruments for LDO incidence. More speci...cally, we use the interaction of di¤erence in slopes (instrument for travel time) with ‘district malaria* inland water’(instrument for LDO incidence) as an instrument for the interaction e¤ect.

# 5. Data

The main data source for the estimation of the wage regressions is the Household Income and Expenditure Survey, 2002 (HIES, 2002). We use the rural sub-sample of Sri Lanak HIES 2002. The HIES 2002 collected information from a nationally representative sample of 16,924 households drawn from 1913 primary sampling units. The survey covered 17 of Sri Lanka’s 25 19