rafmacalaba/datause-encoder-data huggingface dataset:
We also provide new evidence on gender differences in tax compliance. Prior research indicates that women are generally more compliant with tax filing and reporting obligations compared to men (Kleven, Knudsen, Kreiner, Pedersen, and Saez, 2011; Asmare and Yimam, 2020; Cabral, Gemmell, and Alinaghi, 2021). Several key factors have been proposed to explain this disparity, including women’s higher risk aversion (Croson and Gneezy, 2009), stronger tax morale, disparities in tax declaration and enforcement processes (Ambel and Woldeyes, 2024), and genderspecific social norms that interact with gaps in literacy, employment type, and access to information, among others (Komatsu, Shaukat, and Ozer, 2024). Our granular administrative data enables us to offer gender-disaggregated compliance insights on property taxation, in a low-enforcement setting, finding no meaningful gender differentials. Our finding contrasts with earlier studies, which suggested that women experienced either lower effective tax rates due to exemptions for lower-valued properties—more commonly owned by women in São Paulo, Brazil (Scot et al., 2023)—or, as Komatsu et al. (2021) found, a heavier tax incidence for female-headed households based on survey data from rural Ethiopia.

Lastly, while there is ample evidence on the effect of nudges—such as deterrence letters—on tax compliance and collection (Antinyan and Asatryan, 2024), research linking compliance and gender remains limited (see, for example, López-Luzuriaga and Scartascini, 2023; Awasthi et al., 2023). Hence, the results from this project exhibit great promise of informing policy debates and the conduct of tax policy that contribute toward the achievement of gender equality goals.

The remainder of the paper is organized as follows. In section 2, we describe the institutional context. Section 3 details the sources and composition of our tax data. Section 4 characterizes residential property ownership in _Tres de Febrero_ by gender. Section 5 brings three stylized facts on property tax compliance and also leverages experimental evidence on differences in compliance responses across genders. Finally, Section 6 discusses some policy implications behind our results and then concludes.

# **2 Institutional Context**

Tres de Febrero is an urban municipality (county) in the Greater Buenos Aires metro area, Argentina. As of 2022, it had approximately 365,000 residents and 115,000 households, making up 1.2% of the total population of Argentina (INDEC, 2022). It has the third highest population density in the province of Buenos Aires, with great connectivity and accessibility to neighboring areas, and contributes 2.4% to the total urban tax valuation of the province, ranking 13th among the 135 municipalities in fiscal valuation.

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Croson, R. and Gneezy, U. (2009) “Gender Differences in Preferences,” _Journal of Economic Literature_ , 47 (2): 448-474.

Dewaelheyns, N. and Van Hulle, C. (2008). _Small Business Economics_ . 31(4): 409-424.

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Eslava, M. and Haltiwanger, J. (2014). “Young Businesses, Entrepreneurship, and the Dynamics of Employment and Output in Colombia’s Manufacturing Industry”, **mimeo** , http://www.banrep.gov.co/sites/default/files/eventos/archivos/sem_11_cali.pdf Fackler, D., Schnabel, C. and Wagner, J. (2013) “Establishment exits in Germany: The role of size and age”, Small Business Economics 41:683–700 Fariñas, J. and S. Ruano. (2005). “Firm Productivity, Heterogeneity, Sunk Costs, and Market Selection”. _International Journal of Industrial Organization,_ 23:505-534.

Foster, L., Haltiwanger, J. and Krizan, C. J. (2001) Aggregate Productivity Growth Lessons from Microeconomic Evidence, in New Developments in Productivity Analysis (2001), (editors) Charles R. Hulten, Edwin R. Dean and Michael J. Harper, (p. 303 - 372) University of Chicago Press Foster, Lucia, John Haltiwanger, and Chad Syverson. 2008. “Reallocation, Firm Turnover, and Efficiency: Selection on Productivity or Profitability?" _American Economic Review_ , 98(1): 394-425.

Faccio, M., Marchica, M.T. and Mura, R., (2014). “CEO Gender and Corporate Risk-Taking”, http://ssrn.com/abstract=2021136 Frazer, G. (2005) “Which Firms Die? A Look at Manufacturing Firm Exit in Ghana” _Economic Development and Cultural Change,_ 53 (3):585-617.

Gelübcke, J., and Wagner, J (2012). “Foreign ownership and firm survival: First evidence for enterprises in Germany”, _Economie Internationale_ , 132:117-139.

Haltiwanger, J. (2012) Job Creation and Firm Dynamics in the U.S., in NBER Book Series Innovation Policy and the Economy, (editors) Josh Lerner and Scott Stern, (p. 17-38) University of Chicago Press Hallward-Driemeier, M. and Rijkers, B. (2013) “Do Crises Catalyze Creative Destruction? FirmLevel Evidence from Indonesia”, _The Review of Economics and Statistics,_ 95(5):1788-1810.

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probability of a self-fulfilling crisis at a specific value _π_ , 0 _≤ π ≤_ 1. The timing within each period is like that in Cole and Kehoe:

1. The shock _ζ_ realizes, the aggregate state is _s_ = ( _B, z−_ 1 _, ζ_ ), and the government chooses how much debt _B_<sup>_′_</sup> to sell.

2. Each of a continuum of measure one of international bankers chooses how much debt _b_<sup>_′_</sup> to purchase. In equilibrium, _b_<sup>_′_</sup> = _B_<sup>_′_</sup> .

3. The government makes its default decision _z_ , which determines _y, c,_ and _g_ .

Given this timing, we can reduce the government’s problem choosing _c_ , _g_ , _B_<sup>_′_</sup> , _z_ to solve International bankers are risk neutral with discount factor _β_ so that the bond prices _q_ ( _B_<sup>_′_</sup> _, s_ ) are determined by the probability of default in the next period. There is a continuum of measure one of bankers. For further details please refer to Conesa and Kehoe (2017). The solution for the international bankers’ utility maximization problem implies that if internationalwhere<sup> ̄</sup> _b_ is thebankerslower dothresholdnot lend.and _B_ ̄ifis _B_ the<sup>_′_</sup> _≤_ upper<sup> ̄</sup> _b_ the governmentthreshold anddoesif ̄ _b_ not _< B_ default<sup>_′_</sup> _≤ B_ ̄,eventhe government does not default if international bankers lend. If _B_<sup>_′_</sup> _> B_<sup> ̄</sup> the government defaults even if international bankers lend.

To solve for the equilibrium, we choose the same functional form for the utility function as in Conesa and Kehoe (2017), For the equilibrium definition and further details please refer to Conesa and Kehoe (2017) and Cole and Kehoe (1996, 2000).

The framework identifies thresholds that distinguish three zones of debt that rely on calibrations for each country:

- In the safe zone, the government would not find it optimal to default even if there is a panic in financial markets and it could not roll over its stock of debt. The debt ratio for the countries in the safe zone is relatively small. Hence, the optimal strategy is to be solvent and sacrifice consumption to repay the stock of debt, rather than experiencing an output loss because of an insolvency.

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and negatively correlated with the absolute difference in reported ERRs in the PAD and ICR. The larger the project, the smaller this difference. This again suggests that more care may have been given to the quality of economic analysis in larger projects, independent of the task team effect, which is insignificant. The coefficient on the inflation variable becomes significant when the project size is also entered into the regression, suggesting some cross effects between these two variables.

**Table 7: Average ERRs and their differences by GP, 1975‐2015**

||Average<br>ERR at<br>appraisal|N|Average ERR<br>at<br>completion|N|Mean<br>difference<br>between<br>the two<br>ERRs,%|N|Median<br>difference<br>between<br>the two<br>ERRs,%|Standard<br>Deviation<br>of the<br>differences|
|---|---|---|---|---|---|---|---|---|
|Agriculture|24.7|1,284|17.5|1,103|‐25.8|1,050|‐26.5|60.3|
|Education|19.8|35|22.2|31|11.7|19|0.2|71.2|
|Energyand Extractives|22.5|661|19.3|607|‐9.4|582|‐14.5|74.7|
|Environment & Natural Resources|20.2|29|24.2|26|12.2|21|0.0|68.4|
|Finace,markets,Trade & competitiveness|33.3|46|29.5|27|49.9|23|25.0|110.0|
|Governance|84.8|14|113.1|6|‐22.2|4|‐25.8|57.1|
|Health Nutriton & Population|43.3|24|42.5|16|‐10.4|9|0.0|40.8|
|Macroeconoimcs & Fiscal Management|156.0|1|0.0|‐|0.0|‐|‐|‐|
|Social Protection & Labor|29.9|13|25.3|9|18.2|4|‐9.4|72.1|
|Social,Urban,Rural and Resilience|23.1|195|23.0|164|‐4.6|136|‐10.8|66.1|
|Transport & ICT|30.0|951|28.1|852|‐0.5|830|‐5.8|59.2|
|Water|15.6|257|13.2|216|‐13.9|199|‐16.7|66.7|
|Povertyand Equity|‐|‐|‐|‐|‐|‐|‐|‐|
|World Bank|25.4|3,510|21.4|3,057|‐12.1|2,877|‐15.44|65.5|

Source: IEG database and staff calculation.

*The difference between the two ERRs is calculated for every project reporting an ERR at appraisal and completion as: 100*(ERR at completion – ERR at appraisal)/ERR at appraisal. The mean difference was then taken on the percent of differences.

**Model 3 Results:  Does EA matter to the success of a project, after controlling for country, project and team effects?**

The results for model 3, which examines how the frequency and discrepancy in ERRs are correlated with project performance, are summarized in Tables A.6 to A.9. OLS regressions are estimated for the case where the dependent variable is the project rating on the 6 point scale. Logit regressions are used for the binary dependent variable where project performance is represented as either successful or unsuccessful.

Tables A.6 and A.9 show that reporting the ERR in both the PAD and ICR is strongly and significantly associated with project performance. Tables A.8 and A.9 show that the discrepancy between ERR reported in the PAD and ICR is negatively and significantly associated with project performance. Specifically, the wider the discrepancy (after controlling for the optimism bias at project preparation), between the ERR reported in the PAD and ICR, the lower the project performance. These regressions provide strong evidence for the impact of the quality of project economic analysis on project performance, with results that are robust across the various regression specifications and estimation methods.

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reasonably well, there is thus considerable scope for better access to reasonably reliable information on property ownership to improve the functioning of financial markets. This is relevant for policy given the time and cost involved in establishment and maintenance of a full-fledged titling system.

While the ability to demonstrate a credit effect sets our paper apart from other studies, we note that, especially if compared to the estimated impact of stamp duty reductions and the overall expansion of credit supply during the period under concern the estimated magnitude of this effect is small, its outreach limited to urban property owners, and its impact on land markets and allocative efficiency negligible. In fact, the evidence of registration being very price elastic found here suggests that regulatory reforms are likely to lead to the desired results only if they provide affected parties with tangible benefits the magnitude of which exceeds the cost of formal registration. By implication, the costs of registering most types of property transfers in AP remain high compared to the benefits. This illustrates that, while computerization of existing systems can provide benefits, more far-reaching measures are likely to be needed to broaden and deepen these effects. In the case of AP, the relative success of computerizing land registries did not prompt adoption of more far-reaching property reforms, suggesting that the link between ‘quick wins’ and more far-reaching reform efforts is not automatic<sup>.10</sup> One of the underlying reasons may be that successful initial reforms do not unequivocally identify the areas on which subsequent efforts should focus.

The fact different Indian states have taken a variety of routes to improve the functioning of their land administration systems implies that similar study for other states, especially those with approaches significantly different from the one taken in AP, can provide insights on the magnitude and distribution of the economic effects to be expected from property rights interventions. Prime among these are efforts to integrate land records and registries and to improve local access, e.g. through kiosks established in partnership with the private sector. Evidence from other states can also provide an opportunity to quantify and analyze effects of land administration reform on governance and corruption, an area that is of great importance in the Indian context empirically but on which little information was available in our case. Both the methodological and substantive lesson from this study could be of great relevance beyond India.

> 10 The Indian Government has adopted a large national program of land records modernization that with a volume of US $ 0.5 bn. over the next 4 years but take-up by states has been low.

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been rising by 6 months per annum in order to reach the 65/60 mark by 2012. While 35 years of service is required to be a pension recipient, prorated pensions are available after 15 years of service.

The monthly old-age pension is composed of a base pension, the minimum pension, and an increment that reflects the length of contribution history. Due to differences in standards of living, rural pensioners have a lower base pension than their urban counterparts. The pension contribution rate was 29.9 percent of which 71.2 percent are covered by the employer. The high contribution rate is believed to drive the steady decline in labor force formalization and the rate of participation in old-age pensions among private businesses since transition.

Furthermore, the taxable salary cannot be more than five times the minimum wage, while the maximum amount of pension received by an individual cannot exceed twice the minimum pension. These restrictions encourage individuals to underreport earnings/time worked and to work for fewer years since working substantially longer will not bring them higher benefits. Hence, while the private sector is supposed to pay better salaries than the public sector, more than 50 percent of private sector workers are declaring minimum wages as only 1 percent of public sector employees are declaring minimum wage. Lastly, although approximately 372,000 people are estimated to be above the retirement age, more than 440,000 are currently pension recipients. The discrepancy is in part due to the failure of families to inform the Social Insurance Institute (SII) that the pensioner has died and that the pension should be terminated.

# **3. Albanian Labor Market Dynamics**<sup>**9**</sup>

Since the collapse of the pyramid investment schemes in 1997, Albania’s GDP has grown on average roughly 8 percent each year. Yet, as a result of improved allocation of production

> 9The findings presented in this section are obtained from World Bank (2006b), unless otherwise stated.

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**Figure 1a: Evolution of export volumes, 1990 to 2012**

<!-- Start of picture text --> 1,400<br>1,255<br>Total wine production<br>1,200<br>All wine exports<br>1,000 Bottled wine exports<br>800 743.9<br>600<br>405.8<br>400<br>200 187<br>43.1<br>0 22.7<br>MM Litres<br>1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012<br><!-- End of picture text --> The increase in export volumes between 1990 and 2012 is mirrored by equally spectacular increases in export values<sup>5</sup> : from $116 million to $1.78 billion for total wine exports (or 13.2 percent per annum, 23 percent per annum over the 1990s and 5.6 percent per annum thereafter), and from $89 million to 1.35 billion for bottled wine exports (or 13.1 percent per annum, again 23 percent per annum over the 1990s and 5.5 percent per annum thereafter). Figure 1b shows the evolution of export unit values over time, with a significant price premium for bottled wine over all wine exports (taking into account that the highervalue bottled wine exports are also included in total exports). However, it is striking that bottled wine unit values have not increased further over time, suggestive of the continuing predominant niche of most Chilean wines as relatively low-cost “value for money” products. Figure 1b also shows, on the right axis, the evolution of the share of bottled wine exports in total exports by volume over time, with the share remaining relatively constant at approximately 55 percent, with a low of 39 percent in 1994 and a high of 61 percent in 2011 – highlighting that the mix of export volumes has not shifted significantly toward higher-value wines.<sup>67</sup>

> 5 All figures throughout the study are reported in constant (2012) US dollars, unless otherwise noted.

> 6 The share of bottled wine exports has also remained fairly constant over time, beginning the period at 77 percent in 1990 and ending at 76 percent in 2012, with a low of 67 percent in 1993 and a high of 82 percent in 2007.

> 7 As a signal of what is possible and the global brand image that Chile has attained, Concha y Toro has consistently been rated in the top 3 most valuable wine brands in the world from 2006 through 2013, according to an annual compilation of the top 100 spirits and wine brands (Intangible Business). These global rankings are based on objective measures such as market share, brand growth, price positioning, and number of markets with a significant brand presence, together with a range of subjective measures.

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are other cases in which the proposed treatment of risk makes a significant difference. Implementation of a systematic treatment of riuk in project appraisal will be greatly simplified if a general class of country and sector combinations for which risk can safely be neglected can be identified so that efforts can be concentrated on the remaining categories where it does matter.

# VI. DIRECTIONS FOR FURTECR WORK

We believe that the exploratory research has yielded results of sufficient interest and promises to warrant further and more detailed study. Some ideas for this emerge naturally from the work reported here.

The first step is to improve the procedure for forecasting the coefficients of variation and the correlation coefficients. We ran a least squares regression for each time series by itself and then put together the residuals to calculate covariances. A vector autoregression, or treating several time series as a system of seemingly unrelated regressions, would be an improvemen.t but was too time-consuming for a pilot study. Even more general methods, including analogs of the estimation of time-varying betas in financial economics (Szeto, 1973), or more sophisticated time series specifications like the ARCH model of Engle (1982), can also be tried if the work proceeds.

Our next suggestion is to use this method to carry out fresh ex ante appraisals of some projects previously examined in the Bank. This will show how the incorporation of risk considerations alters the assessment of some actual projects. We may even find a partial explanation
# **Table S6.S: Results for the baseline specification with the geographical distance variable omitted**

||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|
|---|---|---|---|---|---|---|---|---|
|VARIABLES|newprod|invdum|anyrd|it|pcf_tech|suprat|htrain|ftrain|
|supbuy|0.0135|-0.203|-0.301**|0.520|-0.247|-0.0958|-0.0965|0.370|
||(0.350)|(0.326)|(0.122)|(0.543)|(0.198)|(0.0877)|(0.263)|(0.342)|
|samesup|-0.0810|-0.153*|-0.145**|-0.206*|-0.256**|-0.00965|0.0552|-0.0183|
||(0.0731)|(0.0784)|(0.0617)|(0.106)|(0.127)|(0.0439)|(0.0839)|(0.0521)|
|samecus|0.0244|0.00572|0.130***|0.241***|0.188*|-0.0420|0.0868**|0.0212|
||(0.0224)|(0.0343)|(0.0347)|(0.0601)|(0.101)|(0.0288)|(0.0366)|(0.0709)|
|same_sec|0.00462|-0.00131|-0.0138|-0.0963***|-0.0307|0.00222|-0.0344*|-0.00870|
||(0.0101)|(0.0134)|(0.0185)|(0.0299)|(0.0311)|(0.00627)|(0.0189)|(0.0159)|
|ad_fmage|0.000122|0.000257|0.000346|-0.00323***|-0.00104|-0.000515*|-0.000440|0.000881|
||(0.000281)|(0.000370)|(0.00101)|(0.00123)|(0.00132)|(0.000303)|(0.000640)|(0.000998)|
|ad_meduc|0.00582|0.0406***|0.00240|0.00948|0.0592**|0.00516|-0.00374|-0.0146***|
||(0.00632)|(0.0144)|(0.00895)|(0.0167)|(0.0230)|(0.00339)|(0.00561)|(0.00464)|
|ad_mexper|-2.91e-06|-0.000304|-0.000468|-0.000150|-0.000218|0.000276|-0.00160***|0.000634|
||(0.000287)|(0.000266)|(0.00112)|(0.00213)|(0.00234)|(0.000598)|(0.000508)|(0.00108)|
|ad_mfemale|0.000903|0.0358*|0.106***|0.449***|0.252***|0.0277|0.0497|0.0849|
||(0.00631)|(0.0190)|(0.0394)|(0.0901)|(0.0758)|(0.0176)|(0.0375)|(0.0543)|
|ad_lemp|<br>0.0231**|<br>0.0525***|<br>0.0404**|<br>0.169***|<br>0.199***|<br>0.0179***|<br>0.0574***|<br>0.0780***|
||(0.00914)|(0.0143)|(0.0176)|(0.0424)|(0.0457)|(0.00572)|(0.0170)|(0.0205)|
|Constant|0.462***|0.371***|0.281***|0.418***|0.738***|0.304***|0.346***|0.0941***|
||(0.0170)|(0.0292)|(0.0351)|(0.0647)|(0.0620)|(0.0148)|(0.0336)|(0.0316)|

Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1 45
**Table 2.6   KIBS sector growth in Singapore, 1990-2001**

||Establishments|Employment|Operating Receipts<br>($million)|Value Added<br>($million)|Value added/ Labor<br>($’000)|Value added/Firm<br>($’000)|
|---|---|---|---|---|---|---|
|1990|2,522|23,042|2,051.9|1,130.9|49.1|448.4|
|1995|5,005|45,023|6,293.9|3,037.3|67.5|606.9|
|1996|5,437|46,054|6,342.0|3,279.6|71.2|603.2|
|1997|6,396|50,195|7,414.9|3,780.4|75.3|591.1|
|1998|6,767|57,808|8,157.3|3,897.1|67.4|575.9|
|1999|6,807|62,677|9,223.3|4,451.5|71.0|654.0|
|2000|6,789|65,766|10,416.4|4,935.9|75.1|727.0|
|2001|8,771|71,199|10,918.0|5,077.9|71.3|578.9|
||||Compound averag<br>|e annual growth rate<br>|(%)<br>||
|1990-2001|12.0|10.8|16.4|14.6|3.5|2.4|

_Note_ : KIBS data includes the following industries: IT and related services, legal activities, market research, business & management consultancy activities, engineering services, architectural, quantity surveying, building & appraisal services.

# _Sources_ :

Singapore Department of Statistics (DOS). (various years). _Economic Surveys Series: Business Services and Real Estate_ . Singapore: DOS. Singapore Department of Statistics (DOS). (2001). _Economic Surveys Series 2001: Architectural, Engineering & Technical Services._ Singapore: DOS. Singapore Department of Statistics (DOS). (2001). _Economic Surveys Series 2001: IT & Related Services._ Singapore: DOS. Singapore Department of Statistics (DOS). (2001). _Economic Surveys Series 2001: Professional Services._ Singapore: DOS.

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