rafmacalaba/datause-encoder-data huggingface dataset:
mation reporting and withholding agents), as suggested theoretically by Kopczuk & Slemrod (2006) and Kleven et al. (2016), and demonstrated empirically by Best (2014) in the context of employer reporting on employees' earnings. In addition, our results contribute to the empirical literature on third-party reporting and compliance. Consistent with Naritomi 2015 and Pomeranz 2015, we show that expanding the coverage of information reporting increases reported taxable income substantially. We can also reconcile these ndings with Carrillo et al. 2016 and Slemrod et al. 2015, who provide evidence of evasion shifting to the cost margin. Indeed, our analysis suggests that most rms are responsive to the presence of third-party reporting when they are aware of such reporting ex ante, but the remaining misreporters are not responsive to requests to correct their reports ex post. Put dierently, most rms voluntarily comply on third-party reported margins, but enforcing compliance among the remaining non-compliers is dicult.

Second, our study extends the literatures on tax withholding and the impact of defaults. A large literature has analyzed withholding for the personal income tax, focusing mostly on the United States (Barr & Dokko 2008, Gandhi & Kuehlwein 2014, White et al. 1993, Highll et al. 1998). Aside from descriptive policy reports (Samanamud 2013, OECD 2009) and legal writing (Soos 1990), the only study analyzing withholding on rms is Carillo et al. (2012). They show that rms bunch at a withholding rate kink, and interpret this as evidence for a (perceived) discontinuity in the audit function. Our paper is the rst to quantify the tax revenue impact of withholding for rms, and identify the impact mechanisms. By showing that witholding establishes a compliance default, we contribute to the behavioral literature on defaults, which shows that defaults increase organ donation (Johnson & Goldstein 2003) and retirement savings (Chetty et al. 2014, Thaler & Benartzi 2004, Madrian & Shea 2001). We show that a default can also be used to induce people into a behavior such as tax compliance that even rational agents may not display.

Finally, we draw on methodological contributions from two literatures. We follow the lead of Fisman & Wei (2004) in identifying misreporting by comparing two data reports on the same tax base. This approach is also used in Zucman (2013), Kumler et al. (2015), Best (2014) and Rijkers et al. (2015). Using the approach, we show that rms under-report sales as well as costs, consistent with Carrillo et al. (2016). We also construct novel estimates of compliance gaps on the extensive and payment margin. Shedding light on payment delays, we highlight the importance of analyzing payment data in addition to tax liability data, which previous studies have focused on. We also draw on the bunching literature in public nance, initiated by Saez (2010), Chetty et al. (2011) and Kleven & Waseem (2013), and summarized in Kleven (2016). This literature provides the techniques to estimate taxpayers' behavioral responses to discontinuities in the tax schedule, and translate them into income elasticities.

5
property. Finally, we also examine other environmental variables, such as the presence of an educated labor force.

Taken together, our results suggest that while bureaucratic entry requirements seem to be motivated by private interests, it is by no means obvious that the best way to encourage entry and competition is to eliminate all regulation. The absence of some regulations can also be an effective entry barrier (see Rajan and Zingales (2003, a, b)). Regulations that expand access to finance and human resources seem to help entry even while those that directly screen entrants hurt entry.

In a related paper, Desai, Gompers, and Lerner (2003) use a cross-country approach and also find that entry regulations have a negative impact on firm entry. The cross-country approach has a number of limitations including variations in coverage in the database across countries, which is why we have chosen a within country, cross industry approach. Nevertheless, their findings are complementary to ours. Another paper that is closer in methodology to ours is Di Patti and Dell’Ariccia (forthcoming). They examine whether entry is higher in informationally opaque industries in Italian regions that have a more concentrated banking sector (they find it is). Their use of the Rajan and Zingales methodology is similar to ours, but the environmental variables they focus on, as well as the data they use, are very different. In another related paper, Bertrand and Kamarz (2002) examine the expansion decisions of French retailers following new zoning regulations introduced in France. They find a strong relation between increases in entry deterrence (such as rejection of expansion or entry decisions) and decreases in employment growth. A cross-country study related to ours is Scarpetta et al. (2002), who use firm-level survey data from OECD countries to analyze firm entry and exit. They find that higher product market and labor regulations are negatively correlated with the entry of small- and medium-sized firms in OECD countries. Unlike us, however, they do not focus on country and industry interaction effects.

6
Policy ReseaRch WoRking PaPeR 4465

# **Abstract**

China is often mentioned as a counterexample to the findings in the finance and growth literature since, despite the weaknesses in its banking system, it is one of the fastest growing economies in the world. The fast growth of Chinese private sector firms is taken as evidence that it is alternative financing and governance mechanisms that support China’s growth. This paper takes a closer look at firm financing patterns and growth using a database of 2,400 Chinese firms. The authors find that a relatively small percentage of firms in the sample utilize formal bank finance with a much greater reliance on informal sources. However, the results suggest that despite its weaknesses, financing from the formal financial system is associated with faster firm growth, whereas fund raising from alternative channels is not. Using a selection model, the authors find no evidence that these results arise because of the selection of firms that have access to the formal financial system. Although firms report bank corruption, there is no evidence that it significantly affects the allocation of credit or the performance of firms that receive the credit. The findings suggest that the role of reputation and relationship based financing and governance mechanisms in financing the fastest growing firms in China is likely to be overestimated.

This paper—a product of the Finance and Private Sector Team, Development Research Group—is part of a larger effort in the department to study the role of formal versus informal finance in development. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at ayaptenco@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
quintiles.

# **2.2.1 A geographic or genetic artifact?**

Perhaps people who live in certain countries or regions tend to be tall or short, and this is coincidentally correlated with open defecation. Is the result driven by certain countries or regions, or fixed differences such as genetics?

Figure 3 presents initial evidence against this possibility. The sample is restricted to countries with more than one DHS observation, and country means across collapsed DHS surveys are subtracted from the height and sanitation survey averages. The figure plots the difference in a country-year’s height from that country’s mean across DHS surveys against the difference in sanitation. The slope is similar to the undifferenced plot. Moreover, panel (b) continues to demonstrate an association despite not including any data from India.

Returning to table 1, column 4 adds country fixed effects. A control is also added for the average height of mothers of measured children; this is in anticipation of a possibility observed by Deaton and Dr`eze (2009) and considered in more depth in section 4.3 that Indian stunting is not caused by current nutritional deprivation or sanitary conditions, but is instead an effect of historical conditions that stunted the growth of women who are now mothers, restricting children’s uterine growth. DHS surveys are categorized into six global regions;<sup>5</sup> column 5 adds six region-specific linear time trends<sup>�</sup> _r_<sup>_δryeary_, to rule out that the effect is driven by</sup> spurious changes in specific parts of the world. Neither of these additions importantly change the estimate of the coefficient, although adding so many controls increases the standard errors.

Table 2 further confirms that no one region is responsible for the results. The association between height and sanitation is replicated in regressions that omit each of the six world regions in turn. The coefficient near 1 notably remains when South Asian observations are

> 5The regions are sub-Saharan Africa, South Asia, the Middle East & North Africa, Central Asia, East & Southeast Asia, and Latin America.

10
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# **4 Conclusions**

Our work has highlighted two sets of concerns about muscular industrial policy action by globally significant economies. First, we confirm a conventional concern that subsidies limit access to markets. When these markets are large, the repercussions are likely to be global and the negative effects cannot be avoided by exporters. Two decades ago, agricultural subsidies in large developed markets provoked the most concern. Now we also need to consider the implications of industrial subsidies for industrial development and economic diversification in trade partners, especially developing countries.

Second, we identify a new concern arising from the combination of industrial policy and PTAs. Non-members of PTAs already faced the cost of exclusion, as PTAs preferentially reduced explicit trade barriers like tariffs through reciprocal liberalization and implicit barriers like technical regulations through mutual recognition and harmonization. Now, exporters from non-member states are further disadvantaged relative to producers within the PTAs that are shielded from the adverse impact of industrial policies. In fact, producers in all PTA members may benefit from subsidies in one member if value added in any member can help meet “local content” eligibility conditions. Non-member countries may therefore lose further market share in PTA regions, even if their goods or services are competitively priced and of higher quality compared to those produced within the PTAs.

A broader concern is about the likely evolution of the global trading system. The synergy between PTAs and proactive industrial strategies could create a more insular and protectionist global trading environment clustered in blocs. The blocs may prioritize internal economic goals over global trade norms and set higher barriers that further isolate non-members. As these trade blocs become more self-sufficient and less reliant on external trade, those outside may find fewer opportunities for export growth and diversification. Furthermore, non-members may be compelled to engage in less favorable trade negotiations or to adopt retaliatory measures, thereby escalating global trade tensions and undermining the stability of the international trade system.<sup>10</sup> This scenario, which underscores both the disparity in bargaining power and the broader implications for global trade dynamics and the stability of a peaceful international economic order, calls for additional research on these topics.

Importantly, future research should aim to address at least three issues. First, the availability of more granular data would overcome the limitations of the currently available datasets.<sup>11</sup> Second, it is important to address more convincingly

> 10See Gopinath et al. (2024) for a description of the similarities and differences between the current international situation and the Cold War.

> 11Banares-Sanchez et al. (2023) and Bastos et al. (2024) offer examples of promising new data

12
|Rural Corridors and Biodiversity|Pablo Francisco Herrera|
|---|---|
|Rural Corridors and Biodiversity|Pablo Francisco Herrera|
|Rural Corridors and Biodiversity|Pablo Francisco Herrera|
|Rural Corridors and Biodiversity|Pablo Francisco Herrera|
|Rural Corridors and Biodiversity|Pablo Francisco Herrera|
|Rural Corridors and Biodiversity|Pablo Francisco Herrera|
|Rural Corridors and Biodiversity|Pablo Francisco Herrera|
|Rural Corridors and Biodiversity|Pablo Francisco Herrera|
|Rural Corridors and Biodiversity|Pablo Francisco Herrera|
|Rural Corridors and Biodiversity|Pablo Francisco Herrera|
|CZ - GREEN INVESTMENT SCHEME|Nina Rinnerberger|
|CZ - GREEN INVESTMENT SCHEME|Nina Rinnerberger|
|CZ - GREEN INVESTMENT SCHEME|Nina Rinnerberger|
|CZ - GREEN INVESTMENT SCHEME|Nina Rinnerberger|
|CZ - GREEN INVESTMENT SCHEME|Nina Rinnerberger|
|CZ - GREEN INVESTMENT SCHEME|Nina Rinnerberger|
|CZ - GREEN INVESTMENT SCHEME|Nina Rinnerberger|
|CZ - GREEN INVESTMENT SCHEME|Nina Rinnerberger|
|KG: Implementation of Statistical Master Plan|GregoryKisunko|
|KG: Implementation of Statistical Master Plan|GregoryKisunko|
|KG: Implementation of Statistical Master Plan|GregoryKisunko|
|Eastern Dedicated Freight Corridor - I|Martha B. Lawrence|
|Eastern Dedicated Freight Corridor - I|Martha B. Lawrence|
|Eastern Dedicated Freight Corridor - I|Martha B. Lawrence|
|Eastern Dedicated Freight Corridor - I|Martha B. Lawrence|
|Eastern Dedicated Freight Corridor - I|Martha B. Lawrence|
|Eastern Dedicated Freight Corridor - I|Martha B. Lawrence|
|Eastern Dedicated Freight Corridor - I|Martha B. Lawrence|
|Eastern Dedicated Freight Corridor - I|Martha B. Lawrence|
|Eastern Dedicated Freight Corridor - I|Martha B. Lawrence|
|Eastern Dedicated Freight Corridor - I|Martha B. Lawrence|
|Eastern Dedicated Freight Corridor - I|Martha B. Lawrence|
|Eastern Dedicated Freight Corridor - I|Martha B. Lawrence|
|Eastern Dedicated Freight Corridor - I|Martha B. Lawrence|
|Eastern Dedicated Freight Corridor - I|Martha B. Lawrence|
|Eastern Dedicated Freight Corridor - I|Martha B. Lawrence|
|Eastern Dedicated Freight Corridor - I|Martha B. Lawrence|
|Eastern Dedicated Freight Corridor - I|Martha B. Lawrence|
|Eastern Dedicated Freight Corridor - I|Martha B. Lawrence|
|Eastern Dedicated Freight Corridor - I|Martha B. Lawrence|
|Water Resources and Irrigation Sector Management Program 2|Jun Matsumoto|
|Water Resources and Irrigation Sector Management Program 2|Jun Matsumoto|
|Water Resources and Irrigation Sector Management Program 2|Jun Matsumoto|
|Water Resources and Irrigation Sector Management Program 2|Jun Matsumoto|
|Water Resources and Irrigation Sector Management Program 2|Jun Matsumoto|
|Water Resources and Irrigation Sector Management Program 2|Jun Matsumoto|
|Water Resources and Irrigation Sector Management Program 2|Jun Matsumoto|
standard deviations larger than the mean share of that type of OOP healthcare expenditures in total household consumption with the mean share of those expenditures in household consumption times the respondent’s household’s consumption. That is, for respondent _i_ in household _h_ and OOP type _j_ , we replace _OOPihj_ with the sample mean value of ( _OOPihj_ / _Ch_ ) times _Ch_ , where _Ch_ is household consumption. In all, we change 112 healthcare expenditure records (0.2 percent of the sample) with these procedures.

An important problem with this estimate of OOP healthcare expenditures is that it applies only to expenditures incurred in the past two weeks. But healthcare expenditures in Ghana are not regular or frequent, so if we want to know how much is spent in a year, simply multiplying the reported amounts by 26 will be inaccurate. Survey respondents who happened to have incurred healthcare expenditures in the past two weeks are not the only people who will incur healthcare expenditures through the year, nor will their annual healthcare expenditures be anywhere near 26 times what they spent in the past two weeks.

To address this, we divide the sample into deciles based on consumption per adult equivalent and into NHIS members and nonmembers; 20 subgroups in all.<sup>17</sup> For each respondent, we then draw and sum 26 random values from the distribution of the share of OOP healthcare expenditures in total household consumption for her/his subgroup whether or not she or he reports healthcare expenditures in the past two weeks. We then multiply the sum of the 26 random draws by total household consumption to obtain our estimate of the individual’s annual OOP healthcare expenditure. This assumes that every member of a subgroup has an equal probability of incurring a healthcare expenditure, though the probability can vary across subgroups. In doing so, we ignore the possibility of serial correlation of OOP healthcare expenditures, that is, the possibility that those who report OOP healthcare expenditures in the past two weeks are more likely to have OOP healthcare expenditures in the rest of the year than those who do not. However, simply multiplying observed OOP healthcare expenditures in the past two weeks by 26 assumes perfect serial correlation throughout the year, something that seems much farther from the truth than our assumption of zero correlation. This is particularly so

> 17 We also tried dividing the sample by groups that might be expected to have greater demand for healthcare: (income quartile)-by-(infants/children/adults/the elderly (60+)/women who have been pregnant in the past year)-by(urban/rural); 40 subgroups in all. This produces results of a similar magnitude to our main results but with the risk premium being _higher_ for NHIS members than nonmembers.

9
# Table A2.1: Comparison, US imports subject to SSG action and over-quota <u>imports, 2006</u>

|<br>Product category|Price-based<br>action taken<br>(kg)|Total over-<br>quota imports<br>(kg)|percentage:<br>action taken /<br>o-q total<br>imports|
|---|---|---|---|
|Meat|2,693,980|72,377,576|3.72|
|Milk and dairy products|602,386|108,214,484|0.56|
|Peanuts and preparations ofpeanuts|114,945|6,176,855|1.86|
|Sugar|65,952|495,692,003|0.01|
|Cocoa powder, chocolate products<br>containing sugarandmilk|153,614|14,059,022|1.09|
|Coffee products|31|2,002,814|0.00|
|Short-staple cotton|54|7,504|0.72|
|Allproducts|3,630,962|698,530,258|0.52|

Remembering that imports are screened shipment-by-shipment against trigger prices, the basic point the table makes is that only a few shipments have been subject to SSG measures. The ‘bottom line’ in Table A2.1 is ‘0.5 percent,’ and the base for this figure is the total over the 72 tariff lines over which SSG measures were applied. It does not take into account the other 108 tariff lines that were screened against trigger prices but on which no SSG actions were taken. Even among the products on which some shipments were subject to SSG duties, SSG measures have been applied to a small share of imports. Of on which the United States reported SSG price-based action, the actions were applied to less than 1 percent of imports.

The obvious conclusion is that SSG price-based measures have been applied to a small fraction of imports that are screened for such application.

# <u>Trigger prices compared with import unit values</u>

There are several possible explanations for this low figure:

- The minimum price system works – exporters do raise their prices to avoid paying SSG duties.

- There is sufficient space between US bound and applied tariff rates so that minimum prices (prices at the level of the trigger prices) can be enforced without recourse to the additional duties the SSG allows.

- Import unit values in 2006 were generally above the trigger prices, i.e., above 1986-88 prices.

Of the three explanations, we have looked into only the third. To do so we calculated unit values for each of the tariff lines for which the US had posted upfront trigger prices – and for which we were found import quantity data so that unit values could be calculated. (The reader should not that these unit values are calculated from imports from all sources.) Table A2.2 summarizes our findings.

64