rafmacalaba/datause-encoder-data huggingface dataset:
# **1.1 Related Literature**

Our work connects to several strands of literature. First, we contribute to the literature on firms’ strategies to minimize tax payments. While tax evasion (Slemrod, 2019) and tax avoidance via profit shifting (e.g. see Tørsløv et al. 2022, Bilicka 2019, Beer et al. 2020) received most attention, we document another channel: the use of tax expenditures. The limited evidence we have thus far points to their importance: Klemm (2010) details the types of tax expenditures and argues that they are frequent in low-income countries. Garcia-Bernardo et al. (2022) show that only a moderate share of the fall in ETRs worldwide in recent years is attributable to profit shifting, with the remainder due to domestic tax policy changes, including tax expenditures. Better understanding firms’ use of tax expenditures matters for tax revenue and for economic activity.<sup>5</sup> We are the first to document the extent to which tax expenditures reduce firms’ ETRs in a diverse set of countries.

Second, the literature on tax evasion and avoidance shows that tax minimization strategies strongly vary with firms size: tax evasion rates decrease with firm size (Best et al., 2022; Basri et al., 2019; Bachas et al., 2019), while tax avoidance increases (Gumpert et al., 2016; Davies et al., 2018). Yet, the relationship between tax expenditures and firm size has not been systematically investigated before. We do this with granular data and along the entire (formal) firm-size distribution, uncovering an important non-linearity in the ETR-firm-size relationship.

Third, our work relates to a literature at the intersection of economics and accounting that examines the ETR-firm-size relationship (see Jansk ́y (2022) for a survey and Table A.1 for a summary). These papers differ in their methods (data and ETR definition) and results. We make progress by using tax administrative data for many countries and a common ETR definition. Unlike previously used financial accounts data with narrow coverage in low- and middle-income countries (LMICs), our data cover all formal sector firms. We use an ETR definition that can be measured consistently across countries to expose common patterns in the ETR-firm-size relationship. The previous literature—probably due to methodological differences—has not come to a

> 5 Since tax evasion and avoidance have been shown to have real effects, it is likely that tax expenditures have similar real effects. For instance, Egger and Wamser (2015), de Mooij and Liu (2020) and de Mooij and Liu (2021) show that the tightening of anti-avoidance rules reduced MNEs’ investment in affected destination countries. Su ́arez Serrato (2022) and Bilicka (2022) document labor-market consequences of anti-avoidance rules. Alstadsæter et al. (2022) show that firms engaging in profit shifting pay higher wages for managers, a finding echoed in Souillard (2022).

4
where _β_ s are parameters to be estimated. _Exp/popc_ are exports per capita in country _c_ , and _Bud/popc_ is the budget of the EPA per capita in country _c_ . _GDP/popc_ is GDP per capita measured as the average for the period 2000-2004 in 2005 constant U.S. dollars from the World Bank’s World Development Indicators. _Tc_ is an index of trade restrictiveness imposed by country _c_ on its imports from the rest of the world, _MAc_ is an index of market access restrictions imposed by the rest of the world on exports of country _c_ , and both are borrowed from Kee, Nicita and Olarreaga (2006). _V olc_ is the volatility of the exchange rate in country _c_ , measured by the coefficient of variation of the dollar to local currency exchange rate during the period 2000-2004 obtained from the World Development Indicators. _Regc_ is the number of days it takes to comply with export regulations and procedures from Djankov, Freund and Pham (2006). _F_ & _Rc_ is the geography-determined trade to GDP ratio provided in Frankel and Romer (1999), which was estimated using a trade gravity framework where only geographic variables were used as explanatory variables of bilateral trade flows.<sup>12</sup> _DummiesR_ are regional dummies, and _ec_ is the standard white-noise error. When testing for what works and what doesn’t in EPA modalities we add to (2) the variables discussed in section 3.

We estimate equations (1) and (2) using a full information maximum likelihood (FIML) estimator. The full information maximum likelihood (FIML) is generally more efficient than the two-step approach (LIML), especially in the presence of high levels of correlation between the explanatory variables of the selection and main equations (the two exclusion restrictions we imposed are aid per capita and the log of GDP).<sup>13</sup> We also provide OLS estimates, as

> 12The idea is that EPAs cannot influence the geographic components of trade, such as geographic distance and common borders between trading partners, but their budget may be correlated with the geographydetermined trade to GDP ratio as countries with larger trade flows might provide better funding to their EPAs.

> 13See Puhani (2000) for a survey of the literature. Note however that results of the two-step and the FIML approach were very similar.

15
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31 DR Net Debt-reduction 0 commercial debt/total external debt, World Debt Tables (1990)

# APPENDIX 2:

In this appendix we present the financial sector budget constraint, assuming that all public bonds are held by this sector. The nominal budget constraint of the Central Bank is : (1) CMI + (OBB) + (reserves) + (i - w)(Lg_1) **+** (it - ff)(eR*-l) - (ib - ir)(BB-1 ) - (0L1) + e6R$B where reserves are the commercial banks reserves, OM1 the supply of currency, OBO the remunerated reserves in forms of forced investment or central bank bonds, OL5 the credits from the Central Bank to the public sector and e6R<sup>3</sup> B the international reserves held by the Central Bank.

# The nominal budget constraint of the commercial banks is

(2) OV + (i - ff)(Lp,I) + (ib - if)(BB-1<sup>) + (ib-ff)(B-</sup> 1<sup>) -(im -ir)(V-</sup> 1<sup>) +</sup><sup>**(if**-</sup> ir)(R$b-.1) - 0LD + OBB + OB + eOR$ + (reserves) where OV is the supply of banks deposits, OL, the domestic credit to the private sector, OB the bonds issued by the government and eORSb the international reserves held by the commercial banks.

Substituting equation (2) into (1), we get the budget constraint of the financial sector : ONI3M + OV" - (i. - w)V_1 + (i - r **+** (i - ir)L,_1 + (if - X - eA )eR$_1 + ib(B-l) - OLL + OB + e6R<sup>5</sup> 1 58L where e0R$ - eoR$B + eoR$b

# BibliograRhv

Blejer M. and M.S. Khan, "Government Policy and Private Investment in Developing Countries" IMF Staff Papers, vol.31, june 1984 Blinder A. S., "Credit Rationing and Effective Supply", Economic Journal, vol.97, june 1987 Boehmer E. & W. Megginson, "Determinants of secondary Market Prices for Developing Country Syndicated Loans", The Journal of Finance, vol.XLV, n.5, december 1990.

Borensztein E., "Debt Overhang, Debt Reduction and Investment : the Case of Philippines", IMF working paper, june 1990 Brainard U. and J.Tobin, " Pitfalls in Financial Model Building", American Economic Review (AER), LViii(2), 1968 Claessens S. and I. Diwan, "Methodological Ibsues in Evaluating Debt-Reducing Deals", the World Bank. WPS 408, 1990 Coen R.," The effect of Cash Flow on the Speed of Adjustment", in TaA
with repeat transfers like wages. However, our results indicate that even poor households facing high marginal utility of consumption during the lean season have some capacity to manage cash on hand.

Our paper thus contributes to the literature on the effect of savings defaults albeit in a specific context. We study a one-time transfer, precluding the opportunity for habit formation or learning which may be present in other savings schemes like Save More Tomorrow (Thaler & Benartzi 2004). A key and novel feature is that the transaction costs of saving or dissaving are equalized. Our experiment is thus a strict test of the direct psychological effects of defaults, abstracting from the effects that arise from the asymmetric transaction costs typically present in real-world settings.

We describe our experiment and results in more detail, as follows. Section 2 offers a detailed description of the intervention and timeline. Section 3 describes the data. Section 4 explains our analytical framework. We discuss the effect of savings defaults in Section 5, and the impact of delayed payment in Section 6. We discuss heterogenous treatments effects as robustness checks in Section 7. Section 8 concludes.

# **2 Experimental design**

The windfall income experiment described in this paper is one of a set of interventions designed to encourage savings and understand the mechanisms through which formal bank accounts affect consumption and spending.<sup>2</sup> Crucially, the umbrella project offered subsidized bank accounts with the commercial bank NBS to households in villages located within six kilometers of the bank’s Mulanje branch location.<sup>3</sup> The branch is located in the local trading center, an approximately one-kilometer stretch along the main road with shops, government offices, and branches of other local banks. The field teams completed village listings in ten villages and randomly selected 872 households for surveys and account offers in July 2012. Of those households, approximately five percent already had accounts with NBS and another 15 percent had accounts with one or more other banks. Ultimately, 742 individuals opened new accounts. The final sample included 704 new and existing NBS account holders who participated in the savings promotion studies. From that sample of account holders, a random subset of 600 were selected for the windfall cash experiment.

> 2Other interventions include using labeled accounts and showing respondents a video designed to raise their aspirations about future welfare. Random assignment in the windfall experiment was orthogonal to these other interventions, and controlling for treatment group in other arms of the design does not affect the results in this paper.

> 3Individual household locations were measured via GPS, and could exceed 6 KM.

5
# **References**

- Abadie, Alberto et al. (2023). “When Should You Adjust Standard Errors for Clustering?” _The Quarterly Journal of Economics_ 138, 1–35.

- Acemoglu, Daron and James A. Robinson (2013). _Why nations fail_ . New York: Crown Publishers.

- Addoum, Jawad M, David T Ng, and Ariel Ortiz-Bobea (2020). “Temperature Shocks and Establishment Sales”. _The Review of Financial Studies_ 33, 1331â–1366.

- Adhvaryu, Achyuta, Namrata Kala, and Anant Nyshadham (2020). “The Light and the Heat: Productivity Co-Benefits of Energy-Saving Technology”. _The Review of Economics and Statistics_ 102, 779–792.

- Allcott, Hunt, Allan Collard-Wexler, and Stephen D. O’Connell (2016). “How Do Electricity Shortages Affect Industry? Evidence from India”. _American Economic Review_ 16, 587– 624.

- Anderson, M. (2008). “Multiple inference and gender differences in the effects of early intervention: A reevaluation of the Abecedarian, Perry preschool, and early training projects”. _Journal of the American Statistical Association_ 103, 1481–1495.

- Bakkensen, Laura and Lint Barrage (2018). _Climate Shocks, Cyclones, and Economic Growth: Bridging the Micro-Macro Gap_ .

Bansal, Ravi and Marcelo Ochoa (2011). _Temperature, Aggregate Risk, and Expected Returns_ . Bansal, Ravi, Marcelo Ochoa, and Dana Kiku (2016). _Climate Change and Growth Risks_ . Berkhout, Frans (2012). “Adaptation to climate change by organizations”. _WIRES Climate Change_ 3.

- Bettarelli, Luca et al. (2024). _The Economic Costs of Temperature Uncertainty_ .

- Bilal, Adrien and Diego R. Kanzig (2024). _The Macroeconomic Impact of Climate Change: Global vs. Local Temperature_ .

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**5 |** P a g e

BiH exports growing annually at 33‐34 percent in 2003‐05, its share only slightly increased to 11 percent in 2003‐04 and 12 percent in 2005, mainly because of the re‐entry of the “post‐Kosovo and post‐ Milosevic” Serbia and Montenegro (S&M) into world markets following the 45 percent contraction of total exports in 1999.<sup>2</sup> The conditions surrounding S&M exports growth are strongly reminiscent of the post‐war phase of the BiH export dynamics. The value of S&M exports reached the pre‐Kosovo war level in 1998 only in 2003. The share of S&M in total SEE exports grew from 22 percent in 2001 to 30 percent in 2006. Over the same time period, the share of BiH increased from 11 percent to 15 percent. In 2007, it fell, however, to 14.2 percent.

While the choice of the base year or the use of measures in terms of value may yield slightly different results, the average LSG growth rate in the share of a country’s exports in world imports over 2003‐07 provides a much more accurate measure of export performance. It is not affected by the change in relative prices of exported products and is less sensitive to the choice of a base year: we set it in 2003 as this is the beginning of the expansion phase in BiH exports. Furthermore, the use of mirror statistics puts to rest concerns about the quality of foreign trade reporting by SEE‐6: since most of SEE‐6 exports go to highly developed countries with the best reporting system in the world, they are as reliable as they can get. As can be seen from data presented in Table 1, each SEE has succeeded in increasing its market share in total world markets. Except for Croatia, their average LSG rates were in double digits, with BiH slightly below growth rates achieved by Macedonia and S&M (Serbia and Montenegro).

**Table 1: Dynamics of exports in terms of value of exports and evolving shares in world markets in 2003‐2007 (in percent)**

||LS Growth Rat<br>|e 2003‐07(%)<br>||Export Sh|are in Worl|d Markets|(%)|
|---|---|---|---|---|---|---|---|
|SEE‐5|Export Value|Wld Mkt Share|2001|2003|2005|2006|2007|
|Albania|18.9|4.2|0.0058|0.0064|0.0062|0.0063|0.0078|
|BiH|27.5|12.8|0.0152|0.0166|0.0254|0.0272|0.0282|
|Croatia|17.3|2.6|0.0543|0.0649|0.0715|0.0723|0.0749|
|Macedonia, FYR|27.7|13.1|0.0167|0.0144|0.0185|0.0198|0.0259|
|Serbia and Montenegro|26.7|12.1|0.0254|0.0324|0.0451|0.0476|0.0572|

Source: Based on world import data from the UN COMTRADE Statistics.

Despite impressive growth in the 2000s, BiH as well as SEE region’s exports remain very low: on a per capita, they amounted to US$857 in 2007 as compared to US$ 5,620 for the EU‐8. The value of

> 2 Annual rates of growth of Serbia and Montenegro exports in terms of value were 25 percent and 47 percent in 2003 and 2004 respectively (derived from the UN COMTRADE database).
effect of country level institutions and initial firm size, but extend the analysis to consider other firm-level characteristics, such as ownership and the firm’s legal organization, which while not exogenous to the firm’s outcomes, nevertheless provide descriptive evidence of the association between performance and firm characteristics. Finally, we examine the within-country covariance between firm size and productivity at different points along the lifecycle to get a sense of the extent of misallocation in developing countries.

We use data from the World Bank Enterprise Surveys (ES) database, consisting of 44,870 formal firms<sup>5</sup> in 118 countries, surveyed over the period 2006-2012. The surveys use standardized survey instruments and a uniform sampling methodology to minimize measurement error and to yield data that are comparable across countries. The strength of our data is that we cover most of the developing countries in the world. We have the following main findings: First, our analysis shows that in developing countries, older firms are substantially larger than younger firms. The average firm that is 40 years and older employs 5 times as many workers as the average firm under the age of five. Our results are robust to considering only manufacturing firms and taking into account survey sampling weights. We obtain similar patterns when we look across country income groups. Our results are also robust to excluding firms with government ownership, former socialist economies where there may be a discrepancy in age reported due to large-scale privatization,<sup>6</sup> and also to excluding firms that started operations before countries’ independence. This finding also holds controlling for industry and country fixed effects in a multivariate analysis. The significantly upward sloping age-size profile

> 5 While the Enterprise Survey data surveys establishments, we use the terms firm and establishment interchangeably since we restrict our analysis to single establishment firms.

> 6 The establishments in the survey were explicitly told that if the establishment was privatized, then the establishment year provided should refer to when the original government-owned establishment began operations

4
14 unaccounted-for-water (UFW) due to leaks, old pipes, illegal connections, and a lack of meters. In industrialized countries, UFW values are about 10 to 15 percent . net production while a World Bank study found UFW losses in most Latin American cities ranging from 20 to 50 percent of net production (Yepes, 1992). The revenue losses resulting from these high UFW losses represent an important potential source of funds to improve O&M. In Bogota, the revenue losses have been estimated to be equivalent to 25 percent of total billings. "If captured, these financial resources would have been more than adequate to meet all debt service obligations (UIS$195 million) during this period." In Mexico City, the authorities have no "credible plan to meter consumption, maintain meters, and reduce the number of illegal connections. The magnitude of this neglect, coupled with low rates, requires a federal subsidy in excess of US$1 billion a year (0.6 percent of GDP), an equivalent to the annual sector investment needed to supply the total population of Mexico with adequate water and sanitation services by the end of this century" (Yepes, 1992 p.v.).

As noted in the introduction, establishing institutional and regulatory arrangements that foster efficient water supply systems is complicated by the potential for natural monopolies in **the** collection, purification, and delivery of water. In addition, large numbers of households, many poor, still lack access to decent water supplies, although they have a substantial willingness to pay for a domestic water supply as shown by what they pay private water vendor (World Bank, 1992). One way governments can impiove and extend water supplies is through a program in which the government provides capital for and regulates water supply services while construction is done by private firms and private entities or user groups operate the facilities. In this way, urban and rural communities can reduce government failure while limiting market failures.
|Age=10|(0.1507)<br>0.1437|(0.1449)**<br>0.0577|(0.1439)**<br>-0.1581|(0.1617)*<br>-0.1093|
|---|---|---|---|---|
||(0.1566)|(0.1601)|(0.1898)|(0.1989)|
|Age=11|-0.6396|-0.6792|-0.7562|-0.6909|
||(0.1568)**|(0.1652)**|(0.1721)**|(0.1851)**|
|Age=12|-0.3649|-0.4058|-0.4807|-0.4042|
||(0.1674)*|(0.1702)*|(0.1699)**|(0.1870)*|
|Age=13|-0.1509|-0.2855|-0.4969|-0.3867|
||(0.1727)|(0.1750)|(0.1555)**|(0.1877)*|
|Age=14|-0.3332|-0.4209|-0.5385|-0.4397|
||(0.1524)*|(0.1486)**|(0.1584)**|(0.1758)*|
|Age=15|-0.193|-0.2429|-0.3929|-0.319|
||(0.1346)|(0.1387)|(0.1590)*|(0.1737)|
|Age=16|-0.6085|-0.6758|-0.7647|-0.6702|
||(0.1496)**|(0.1547)**|(0.1547)**|(0.1820)**|
|Age=17|-0.3009|-0.3477|-0.5509|-0.4466|
||(0.1392)*|(0.1401)*|(0.1469)**|(0.1721)**|
|Age=18|-0.2712|-0.2944|-0.5258|-0.421|
||(0.1337)*|(0.1346)*|(0.1495)**|(0.1643)*|
|Age=19|-0.2699|-0.2241|-0.494|-0.1883|
||(0.1805)|(0.1889)|(0.2232)*|(0.2305)|
|Age=20|-0.0812|-0.0648|-0.3339|-0.0723|
||(0.1631)|(0.1603)|(0.1917)|(0.2075)|
|Age=21|-0.8055|-0.7426|-0.8541|-0.6184|
||(0.1673)**|(0.1650)**|(0.1699)**|(0.1904)**|
|Age=22|-0.282|-0.2323|-0.4691|-0.2098|
||(0.2026)|(0.2033)|(0.1900)*|(0.2169)|
|Age=23|<br>-0.416|<br>-0.3827|<br>-0.5638|<br>-0.2998|
||(0.1880)*|(0.1848)*|(0.1969)**|(0.2038)|
|**_Pre-programme share of childr_**|<br>**_en in the populati_**|<br>**_on in region of bir_**|<br>**_th x birth cohor_**|<br>**_t_**<sup>**_(a)_**</sup>|
|Cohort 1: 1-6yrs in 1974||-3.7915|-8.2188|-6.762|
|||(5.7143)|(5.5869)|(5.7790)|
|Cohort 2: 7-12yrs in 1974||-10.0575|-15.6775|-14.5715|
|||(6.3190)|(6.1836)*|(6.4845)*|
|Cohort 3: 13-18yrs in 1974||-0.9922|-2.1929|-3.1051|
|||(6.1626)|(5.9371)|(6.0909)|
|Cohort 4: 19-23 yrs in 1974||26.2996|21.3325|23.291|
|||(7.2262)**|(7.4056)**|(7.5705)**|
|**_Pre-programme enrolment rate_**|**_in region of birth_**|**_x birth cohort_**<sup>**_(a)_**</sup>|||
|Cohort 1: 1-6yrs in 1974|||20.2123|20.5002|
||||(1.8857)**|(1.8678)**|
|Cohort 2: 7-12yrs in 1974|||<br>21.9707|<br>22.0907|
||||(2.4392)**|(2.3538)**|
|Cohort 3: 13-18yrs in 1974|||<br>15.6412|<br>17.6751|
||||(2.0639)**|(2.0431)**|
|Cohort 4: 19-23yrs in 1974|||17.0686|18.7945|

35
Nor has the geographic pattern of agricultural growth in India been particularly pro-poor. The states with higher growth in agricultural yields were not the key states with higher shares of India’s poverty; indeed, there is a mild negative correlation, although not statistically significant (Datt and Ravallion, 2002). Agricultural growth as a whole has also lagged relative to India’s (primarily urban) non-farm economy.

# **_Which country has had more pro-poor growth?_**

In addressing this question we must first confront a semantic point that has been a source of some confusion in recent development policy discussions. “Pro-poor growth” has sometimes been taken to mean that poverty falls more than it would have if all incomes had grown at the same rate (Baulch and McCullock, 2000; Kakwani and Pernia, 2000). This definition focuses on the distributional shifts during the growth process; roughly speaking, for growth to be deemed “pro-poor” the incomes of the poor should grow at a higher rate than those of the nonpoor. By this definition, growth has not been pro-poor in either China or India (after adjusting for the comparability problem in the survey data noted above). In both countries, a distribution-neutral growth process would have had more impact on poverty than actually observed in the 1990s.

However, it is surely problematic to identify a growth process as not being “pro-poor” when the poor benefit as much as they have in India and (especially) China. As the experience of both countries has exemplified, rising inequality during a period of overall economic expansion can come with large absolute gains to the poor. Similarly, a recession will be deemed pro-poor if poor people lose proportionately less than others, even though they are in fact worse off. An alternative definition of “pro-poor growth” proposed by Ravallion and Chen (2003) avoids this problem by focusing instead on what happens to poverty. By this definition “pro-

> and the term in ( ) is the empirical elasticity of non-farm output per capita in state _i_ to national non-farm output per capita. I am grateful to Gaurav Datt for suggesting this calculation.

27