rafmacalaba/data-use-mentions-extended huggingface dataset:
)|Ec. Fr. Index|0.27|0.78|‐0.85|0.20|
|H0:(10),H1:(8)|Ec. Fr. Index|1.65|0.101|‐5.94|0.0|
|Cumulated policy actions (8) versus<br>their level and square(14):||||||
|H0:(8),H1:(14)|CPIA A&B|‐0.69|0.49|1.43|0.076|
|H0:(14),H1:(8)|CPIA A&B|3.64|0.00|‐13.8|0.00|
|H0:(8),H1:(14)|Ec. Fr. Index|0.14|0.885|‐0.48|0.32|
|H0:(14),H1:(8)|Ec. Fr. Index|2.51|0.013|‐11.8|0.00|

The statistics in the first two lines of the table (enclosed in the shaded box with heavy lines) may be interpreted thus: the null that (8) with cumulated policy actions is preferred over (10) with cumulated logged policy actions is not rejected because the P‐value is 0.43, while the null that (10) is preferred over (8) is rejected because the P‐level is 0.004, well below the standard threshold of significance of 0.01 or 0.05. All the tests—within R‐squared, J, and Cox‐Pesaran— point in the same direction, namely that the best‐fitting model is (8).

# (ii) Stationarity and cointegration tests

Since the levels equation includes variables that grow over time, such as GDP
empirical robustness. (Cooper and Cohn 1997) find for a sample of over 500 South Carolina classes a positive effect of merit awards for teachers on mathematics and reading test score achievements.

Cross-sectional studies using data from the American National Educational Longitudinal Survey have been used to show a positive link between individual merit awards for teachers and student test scores (Figlio and Kenny 2007). Positive effects of performance pay have also been found in Arkansas kindergartens (Winters, Ritter, et al. 2009). To mitigate problems of causal inference, sometimes researchers can use difference-in-difference estimation, due to the geographic difference of the phasing-in of reforms (Eberts, Hollenbeck, et al. 2002; Atkinson, Burgess, et al. 2004). While (Eberts, Hollenbeck, et al. 2002) find no effects on student test scores and even slightly negative effects on other outcomes, their analysis relies on student-level data from only two schools. A more thorough and systematic differencein-difference analysis by Atkinson et al. finds clear positive effects of performance pay for British schools. By utilizing particular features of Tennessee's Career Ladder System and the Project STAR field experiment, (Dee and Keys 2004) are able to link teachers' quality assessments, as expressed in the career ladder grouping, to student test scores. They find that the official career ladder system had only mixed success in rewarding teachers with the highest test score gains, but nonetheless teachers with merit awards had positive effects on student's math scores. They found however no statistically significant effects on reading scores.

> 6 An early observational study which revealed significant gaming is noted in (Wilms and Chapleau 1999) who note that performance-based pay began in the UK in about 1710, with salaries based on test scores in reading, writing and arithmetic. The rationale was that it would help keep students from poor families in school, where they could learn the basics. In reality, the incentives encouraged teachers to narrow the curricula to include only easily assessed subjects, and cheating by both inspectors
|Ethnic fractionalization|Ethnolinguistic fractionalization index (measures the<br>probability that two randomly selected persons from a<br>given country will not belong to the same<br>ethnolinguistic group). Source: Mauro, initially from<br>the Atlas Narodov Mira (Departnent of Geodesy and<br>Cartography of the State Geological comnmittee<br>of the<br>USSR, Moscow, 1964) and Taylor and Hudson (World<br>Handbook of Political and Social Indicators, 1972).|
|---|---|
|Middle class share|Share of quintiles 2-4, average 1960-1996.|
|Gini|Average of the period 1900-1996|
|Trust|Percentage of respondents in each nation replying "most<br>people can be trusted". Source: World Values Survey.|
|GDP per capita, PPP|World Development Indicators.|
|GDP per capita growth|Worldl Development Indicators.|

Table lb <!-- Start of picture text --> Institutional Indicators<br>Mean Standard Number of Range<br>Deviation Observaions<br>Voice and Accountability 0.352 0.92 82 -2.5 - 2.5*<br>Quality of the Bureaucracy 3.678 1.46 72 0 -6**<br>Civil Liberties 3.397 1.62 81 1 -7**<br>Property rights & rule-based govemance 3.232 0.82 56 1- 6****<br>Govemment Effectiveness 0.28t 0.94 78 -2.5 - 2.5*<br>Graft 0.2713 1.00 78 -2.5 - 2.5*<br>Law and Order Tradition 3.743 1.40 78 0- 6**<br>Political Instability and Violence 0.116 0.94 78 -2.6 - 2.5<br>Political rights 3.305 1.83
in investment regulation (Lyons and Mayo 2005), and survey responses on the anticipated direction of policy (Barrodale 2010; Engau and Hoffmann 2009). Although some work relies on measures that may capture informal institutions ( _c.f._ Beazer 2012), most recent work has simplified uncertainty theoretically by simply looking at “overall uncertainty”, a broad measure that captures many channels, including informal ones, but evades important questions about the sources of uncertainty(c.f. Kang et al. 2014; Baker et al. 2015; Gulen and Ion 2015). This paper attempts to bridge these perspectives by joining a recent group of papers examining regulatory uncertainty arising from informal institutions and practices, which has so far gone underexplored in the literature.

We begin from the premise that a key source of regulatory uncertainty is _the distance between expectations given de jure regulation and de facto practice_ .<sup>_1_</sup> The further the gap between these two, the less certainty firms have regarding applications of the law and the weaker incentives to invest. We then proceed to argue that unpredictable informal practices surrounding regulation are one important, but underexplored, way in which firms’ expectations can differ from practice. In this paper, we focus on the predictability of two types of informal practice: corruption and state-led attacks on private property.

First, we argue that one source of regulatory uncertainty is corruption, which creates a gap between de facto practices and de jure policy that can be bridged with bribes. Existing work has been ambiguous about the relationship between regulatory uncertainty and corruption (c.f. Triesman 2007), since it is empirically unclear if corruption serves as an unexpected cost of business (Mauro 1995) or a predictable means of cutting through burdensome regulation or attracting state attention (Leff 1964; Slinko et al. 2005). In this paper, however, we draw a distinction between differences in _levels_ of relatively well-ordered (and often centralized) and therefore predictable corruption – a predictable component of the
<br>0.5<br>0.0<br>Power ICT Transport Water<br>% GDP<br><!-- End of picture text --> _Source:_ Private Participation in Infrastructure Database, 2010 .

_Note:_ GDP = gross domestic product; ICT = information and communications technology.

_Continuing the existing strategy of relying on lower-cost technologies could somewhat reduce the funding gap for water and sanitation, but only to a modest extent._ Meeting the MDGs for water supply and sanitation with lower-cost technologies than those that have been used to date (entailing greater reliance on stand posts, boreholes, and improved latrines) could reduce the associated price tag from $348 million to $329 million each year. But the savings, at just under $20 million are relatively small, reflecting the fact that Uganda has already gone a long way toward adopting lower-cost technologies, and the impact on the sectoral and global infrastructure funding gap would be modest.

50
# **5. Individual outcomes and household wealth**

**_Wealth effects on nutritional status:_** Figure 1 plots the incidence of the three anthropometric indices of undernutrition against percentiles of the household wealth-index distribution. For women, we plot incidence for all women 15 to 49 years of age, and for women 20 to 49 years of age, given that younger women typically have a lower BMI. The wealth effect—whereby nutritional status improves with a higher DHS wealth index—is generally evident. However, aside from child stunting, the wealth effect is clearly weak in most countries. The incidence of being underweight is slightly higher for younger women, although the relationship with household wealth is very similar.  Child wasting in some countries shows little or no sign of the wealth effect (notably Gabon, Gambia, Senegal, Sierra Leone and Swaziland). Figure 2 gives the corresponding graphs using household consumption per capita. Similar comments apply.

The overall strength of the household wealth effect for each country can be assessed by regressing the standardized values for nutritional status (that is, the z-score for women’s BMI and height-for-age and weight-for-height z-scores for children) on the wealth index, which (as noted) is also a z-score. The regression coefficient gives the number of standard deviations of the nutritional indicator attributed to a one standard deviation increase in wealth. Table 7 gives results using the DHS, and also the analogous results using standardized consumption z-scores from the LSMS. Although the estimated wealth effects are statistically significant in almost all cases (the exceptions are for child wasting in a few countries), the coefficients appear to be generally quite low; for women’s BMI the mean regression coefficient is 0.26, while it is 0.29 for the height-for-age z-score and only 0.09 for weight-for-height. Even for the countries where the wealth effect on child stunting is highest (Burundi, Cameroon and Nigeria), a one standard deviation increase in wealth is only associated with a 0.5 standard
a homogeneous behavior of countries while CAMU and WAMU countries are subject to asymmetric shocks due to differences in their economic structure.

While recent studies mainly use the panel smooth transition regression (PSTR) method (Kremer, Bick, & Nautz, 2013; Ibarra & Trupkin, 2016; Ndoricimpa, 2017), this paper fills this analytical gap through the analysis of cointegration relationships at the regional and country levels by using panel and country data sets. In this paper, we investigate, through non-linear models combined with cointegration relationship, the threshold level of inflation above which inflation becomes harmful to economic growth for member states of the WAMU and CAMU regions. Models are based on results from Khan and Senhadji (2001) on thresholds, and Faria and Carneiro (2001) on cointegration relationships in the growth-inflation nexus. At the regional level and in each monetary union, we use panel data to analyze a homogeneous cointegration relationship between macroeconomic variables, and the Kao & Chiang (2000) cointegration approach is used to perform this analysis. To show the heterogeneity of this relationship, we use the Stock & Watson (1993) cointegration approach at the country level, and we derive an aggregate regional inflation threshold. We also use ARDL models to check the robustness of the analyses. Results from this study are expected to inform policy makers in CAMU and WAMU countries on the appropriate level of inflation and shed light on the suitability of the 3 percent inflation rate criterion within unions.

Overall, these results show that based on the current inflation thresholds, there are opportunities to increase the current thresholds that are used by the regional central bank in each currency union. By considering a homogeneous cointegration relationship, the inflation threshold above which price increases negatively affect growth would be 5 percent in the CAMU and 2 percent in the WAMU. However, based on the country-level analyses, it could be concluded that it is possible to increase the threshold levels used by both regional central banks: 5.4-5.6 percent in the CAMU, well above the 3 percent
5</sup> Similarly ambitious transport infrastructure projects have not been carried out in post-independence Sub-Saharan Africa. This paper instead relies on the plausibly exogenous annual changes in transport costs induced by world oil price fluctuations, which allow me to determine the short run impact of shocks better than previous work. This does not mean that the changes were small, however, as average annual oil prices varied by a nominal factor of 7.6 during the period of study (1992–2008).<sup>6</sup> These shocks are also of interest because they are more likely to be repeated in the future.

The second related literature is on the scope and drivers of urbanization and urban economic growth in Africa. This literature is almost exclusively cross-country in nature, so that unobserved country-level factors may be confounding results (Fay and Opal, 2000; Barrios, Bertinelli and Strobl, 2006). An exception is Jedwab (2011), who

> 4The eight countries are Benin, Burkina Faso, Cˆote d’Ivoire, Guinea-Bissau, Mali, Niger, Senegal and Togo.

> 5An exception is Buys, Deichmann and Wheeler (2010), who consider the possible effects of road upgrading on _international_ trade, interpreting the relationship between cross-country trade data and road routes between the largest cities in the context of a gravity model.

> 6This corresponds to a real factor of 5.8 using the United States Consumer Price Index (CPI-U).

3
made some sort of payment (Figures 7 and 8).

# **3.3. The Door-to-Door Intervention**

To tackle the growing evasion, the local tax authority created the door-to-door tax enforcement campaign in Kota Gorontalo. It consisted in sending tax officials to properties to directly interact with property owners regarding their tax responsibilities. The program spanned 14 months, from November 2020 to December 2021. Visits peaked in January 2021 with 8,776 monthly visits, but they significantly decreased from March 2021 due to COVID-19, resuming at a slower pace from August to December 2021 when the program was terminated (Figure 6c). If the visitation rate was kept, all properties would have been visited before the end of 2021. By the end of the program in December 2021, of 52,941 registered properties, 31,730 received visits, 59.9% of the total.

The tax officials were equipped with geolocated tablets. Once a visit is entered into the tablet, its location is recorded along with the name of the citizen who answers the door and the name of the person responsible for the property. The visit finishes after the tax official talks to the person responsible for the property or if no one was found at the house. Then, another visit should restart at the next-door neighbor. No house was visited twice.

The geolocation allows us to attest that the visits took place, as well as checking visitation patterns. Our initial analysis shows that the geolocation records are consistent with the registered addresses in our administrative dataset. In Kota Gorontalo, there are 50 neighborhoods. Of the 31,730 visitation records, no geolocation record was located more than 3 km away from Kota Gorontalo. Moreover, only 18 records were distanced more than 500 meters from the neighborhood it was supposed to be.

The high level of autonomy of tax officials in deciding where to visit first has created a major selection of what properties were visited. For example, despite covering almost 60% of the reg14
to 1 and scaling lagged incidence by a calculated susceptible population; and (4) restricting the movements included in calculating imported incidence by removing any movement where the SIM card had no calls or texts for more than two weeks before or after.

One limitation of the mobile phone data is that it only includes mobility within Senegal and cannot incorporate international migration. Immigrants coming in from high malaria

> 29I use a 30km cuto for the spatial correlation and two lags for the autocorrelation.

36
fertility is insufficient, or where the existing ownership structure is already characterized by small to medium-sized holdings, are thus eliminated a _priori._ This gives beneficiaries a better idea of where to focus their efforts, helps to set realistic goals, and puts into perspective the potential contribution of land reform for solving the social problems of a given _municipio._ It increases not only awareness of the scope for land reform as compared to other options aiming at overall development of the municipio (and the degree to which the success of land reform will depend on such complementary measures), but also forces local governments to think about potential levers (from land taxes to land price information systems and training to increase the productive capacity of potential beneficiaries) that they can utilize to

> 25 As highlighted earlier, even under the new land reform law, rationing was largely by non-price means-including outright corruption-and the main challenge for landowners willing to sell was to obtain clearance from the regional and central INCORA offices regarding the availability of funds to purchase their land which was seen as the precondition for proceeding with negotiations.

14
De Mel, Suresh, David McKenzie and Christopher Woodruff (2012). “The demand for, and consequences of, formalization among informal firms in Sri Lanka”, _American Economic Journal: Applied Economics_ , forthcoming.

De Soto, Hernando. (1989). _The Other Path_ , New York: Harper and Row Publishers.

Djankov, Simeon, Rafael La Porta, Florencio Lopez-de-Silanes and Andrei Schleifer (2002). “The Regulation of Entry,” _Quarterly Journal of Economics_ , 117(1): 1-37.

Fajnzylber, Pablo, William Maloney and Gabriel Montes-Rojas (2011). “Does formality improve micro-firm performance? Evidence from the Brazilian SIMPLES program”, _Journal of Development Economics_ 94: 262-76.

Fink, Günther, Margaret McConnell and Sebatian Vollmer (2012) “Testing for Heterogeneous Treatment Effects in Experimental Data: False Discovery Risks and Correction Procedures”, Mimeo. Harvard School of Public Health.

Gibson, John and David McKenzie (2007) “Using the Global Positioning System (GPS) in Household Surveys for Better Economics and Better Policy”, _World Bank Research Observer_ , 22(2): 21741.

Groh, Matthew, Nandini Krishnan, David McKenzie and Tara Vishwanath, (2012). “Soft skills or hard cash? The impact of training and wage subsidy programs on female youth employment in Jordan”, _World Bank Policy Research Working Paper_ no. 6141.

International Finance Corporation (IFC) (2009). _Doing Business 2010: Reforming through difficult times_ . IFC: Washington, D.C.

Jaramillo, Miguel, (2009). “Is there demand for formality among informal firms? Evidence from microfirms in downtown Lima”, German Development Institute Discussion Paper 12/2009.

Kaplan, David, Eduardo Piedra, and Enrique Seira. (2011). “Entry regulation and business startups: Evidence from Mexico” _Journal of Public Economics_ 95(11-12): 1501-15.

Klapper, Leora, Luc Laeven and Raghuram Rajan. (2006). “Entry regulation as a barrier to entrepreneurship
|3.67|4.78|14.06|25.91|28.77|26.97|1.93|1.79|2.12|1.90|
|1 child|2.87|4.62|3.30|4.74|14.23|25.78|30.82|27.79|1.70|2.00|2.06|1.79|
|2 children|3.99|5.87|3.75|4.59|13.16|26.89|25.64|25.95|2.23|1.84|2.34|2.42|
|3 and more children|3.58|6.60|6.21|5.83|16.21|22.99|25.67|24.69|2.23|0.00|1.62|0.60|
|singleparent|2.57|6.50|4.13|5.46|15.59|29.87|28.86|29.83|3.49|3.03|3.71|4.54|

Source: Authors’ estimates based on HSS data.

35
(0.00204)|
|Investment Profile|0.00266|0.00234|0.00220**|0.00255***|0.00313***|0.00301***|0.00333***|0.00341**|0.00300|
||(0.00343)|(0.00158)|(0.00101)|(0.000975)|(0.00106)|(0.00101)|(0.00103)|(0.00160)|(0.00285)|
|Trade Openness|-0.00575|-0.00570|-0.00799|-0.00784|-0.00400|0.00156|0.00296|0.00680|0.00674|
|_(% of GDP, logs)_|(0.0276)|(0.0128)|(0.00817)|(0.00785)|(0.00855)|(0.00815)|(0.00831)|(0.0129)|(0.0229)|
|Financial Openness|0.000159|-0.000632|0.000674|0.00217|0.00180|0.00174|0.00161|0.00203|0.00189|
|_(Chinn‐Ito Index)_|(0.00715)|(0.00330)|(0.00211)|(0.00203)|(0.00221)|(0.00211)|(0.00215)|(0.00334)|(0.00594)|
|_External Factors_||||||||||
|Foreign Growth|0.00173|0.00194*|0.00186***|0.00133*|0.000717|0.000508|-4.78e-05|
Policy Research Working Paper 9921

# **Abstract**

The paper studies the relationship between innovation efforts, innovation outputs, and productivity, using firmlevel data from six East Asian countries. Firms are more likely to invest in innovation when they use technology licensed by a foreign company, are part of a large group, and have a more educated workforce. Investment in research and development can significantly boost both product and process innovation. Product innovation yields significant productivity gains. However, productivity gains from process innovation are not detectable in the sample.

This paper is a product of the Office of the Chief Economist, East Asia and the Pacific Region. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at fdenicola@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
* : Married couple (at least one of whom is at least 18 years old) with children of their and/or the children of others (classified by UNHCR as separated children).

- **Single person** : One adult (person 18 years or older) reporting no other dependents or cohabitees

- **Single caregiver** : One adult living with children of his/her own below the age of 18 and/or separated children and/or one or more elderly persons and/or disabled persons

- **Couple without children** : Married couples (at least one of whom is at least 18 years old) without children or members of their extended family in their own household, includes couples with adult sons and daughters.

- **Unaccompanied children** : Person or group of people below the age of 18 without an accompanying adult.

- **Siblings:** Household of brothers and sisters that share one or both parents, including at least one adult

- **Extended family and other households** : Households with or without children, that include extended family members such as in‐laws, uncles, cousins. An example is married couples or widows/widowers living with their married sons/daughters and their children. Examples of other

> 18 While there is no specific guidance on who should be designated as the principal applicant, UNHCR benefits and food assistance are allocated to this person. It is therefore reasonable to consider the principal applicant as the household head. 19 It is important to note that the JD‐HV data collection is not a randomly selected sample of the ProGres database and that it is designed for targeting. There are three criteria to select cases for Home Visits. The first is newly registered cases, included by default. The second is cases that are due for reassessment. The third refers to urgent cases that require a visit for urgent needs (Verme et al. 2016).

> 20 For example, UNHCR specifically identifies single