rafmacalaba/datause-encoder-data huggingface dataset:
- National Statistical Office (NSO) (2014). Malawi integrated household panel survey 2013 basic information document. Retrieved from

- <u>http://siteresources.worldbank.org/INTLSMS/Resources/3358986</u>

- <u>1233781970982/5800988-1271185595871/6964312-</u>

- <u>1404828635943/IHPS_BID_FINAL.pdf</u>

- Newhouse, D., Shivakumaran, S., Takamatsu, S., & Yoshida, N. (2014). How survey-to-survey imputation can fail. World Bank Policy Research Working Paper Series No. 6961.

- Presser, S., Couper, M. P., Lessler, J. T., Martin, E., Martin, J., Rothgeb, J. M., and Singer, E. (2004). Methods of testing and evaluating survey questions. _Public Opinion Quarterly_ , 68.1, pp. 109–130.

- Tarozzi, A. (2007). Calculating comparable statistics from incomparable surveys, with an application to poverty in India. _Journal of Business & Economic Statistics_ , 25.3, pp. 314– 336.

- Tourangeau, R., Rips, L. J., & Rasinski, K. (2000): _The psychology of survey response_ . Cambridge University Press: New York, NY & Cambridge, U.K.

- Vu, L., & Baulch, B. (2011). Assessing alternative poverty proxy methods in rural Vietnam. _Oxford Development Studies_ , 39.3, pp. 339–367.

17
# **Chapter 2: Calculating Profits**

|**Misconception**|**HB Response**|
|---|---|
|Some people think that counting sales is already enough.|When we did our survey back in March 2016, we asked detailed questions about how people<br>dealt with costs, sales, profits and record-keeping in general. We found that many people gave<br>up calculating profits and some just consider sales as a guide for the performance of their<br>business. The HB shows by means of an idiosyncratic example the consequences of this mistake.|
|Some people think that profits are simply “sales minus product<br>purchases”.|The HB shows by means of an idiosyncratic example the consequences of this mistake.|
|Some people think that profits are “sales minus everything you pay that<br>day”.|The HB shows by means of an idiosyncratic example the consequences of this mistake.|
|Somepeople think calculating profits is complicated.|The HB shows it can be simple.|
|**Re**|**asons to Adopt the Practice**|
|Shops which have records detailed enough that they allow for the shop m<br>sales 42% higher andprofits 45% higher than shops without detailed recor|anager to calculate profits including all major costs to the business are associated with monthly<br>ds or without anyrecords at all.|
|Onlyifyou calculateprofits, you can draw the right conclusions fromyour|records.|
|You may overestimate your profits as you do not account for various bills<br>are outstanding bills to be paid in the future. Conversely, you may have th<br>example to illustrate both cases.|and expenses. As a consequence, you may spend more money than you should, especially if there<br>e impression you are short on money, even if that is not the case. The HB gives an idiosycratic|
household work. For instance, the average Mexican woman spends six hours a day doing unpaid housework, compared to an average of two hours per day for men (World Bank, 2019).

Finally, as a proxy for unearned income, we use the socioeconomic status provided by INEGI as part of the survey. The relationship between the reservation wage and non-labor income is positive only if leisure is a normal<sup>29</sup> good. Under this condition, there is a disincentive effect on entry into the labor market with an increase in unearned income.

Each independent variable takes the form of a dichotomic variable. The same set of proxy variables is considered for each state. In other words, there will be an identical group of exogenous factors for people who do not participate in the labor market, salaried or self-employed work on-site, and salaried or selfemployed telework.

# 5. Results and Discussion

The results are divided into three sections. First, we present the multinomial results for women and explore how the probability changes for the different independent variables. Next, we analyze male teleworkers to see which factors determine their propensity to choose to work from home and test whether those factors differ from female teleworkers. Finally, we run the multinomial for several rounds of the same survey and analyze how the marginal effects have changed over time for male and female teleworkers.

## i. Women

The first two columns in Table 2 in the Appendix show the multinomial coefficients for women in the sample. This table provides us with an idea of women’s characteristics associated with a higher probability of being in a specific state. Each column presents the odds of the outcome category of the dependent variable for working on-site and teleworking, as self-employed or salaried, respectively, compared with the reference category of being out of the labor force.

The level of education is positively associated with teleworking and working on-site regardless of choosing self-employment or not. However, being self-employed is less likely for the youngest cohort between 2224 years old. This is because young people lack access to the capital to build their own businesses. The same is true for the different levels of socioeconomic status and the choice of being self-employed and telework. There is a higher likelihood of being employed for women who have college or more level of education and in particular, a higher likelihood of being teleworkers. For women, children in the household are negatively associated with any type of work.

Given the complexity of interpreting a nonlinear model such as the multinomial, we show the marginal effects in Table 3, which are easier to follow. Each marginal effect represents the average discrete change from 0 to 1 for each outcome category as described in equation (11). In other words, it shows how a discrete change in the independent variable is related to predicted changes in the probabilities of being in a particular state.

> 29 The consumption of leisure increases with the rise in income.

14
Policy Research Working Paper 10221

# **Abstract**

This paper analyzes the risks to child development and school readiness among children under age 6 in Pakistan. Drawing on a nationally representative telephone survey conducted between December 2021 and February 2022, it presents the first nationally representative estimates of child development for children under 3 years of age and school readiness for children 3 to 6 years of age, using internationally validated instruments. The paper examines how risk factors such as parental distress, lack of psychosocial stimulation, food insecurity, low maternal education, no enrollment in early childhood education, and living in a rural area are associated with children’s outcomes. The data indicate that more than half (57 percent) of parents with children under age 3 were distressed and that 61 percent of households reported cutting down on the size of or skipping meals since the start of the pandemic. The data reveal that over half of parents fail to engage in adequate psychosocial stimulation with their child and enrollment in early childhood education is very low (39 percent). The paper finds that child development outcomes decline rapidly as the number of risks increase. Specifically, for children under 3 years, lack of psychosocial stimulation at home and higher levels of parental distress were most significantly associated with lower child development levels. For a child aged 3 to 6 years, early childhood education enrollment and the amount of psychosocial stimulation the child receives at home had the strongest association with school readiness scores.

This paper is a product of the Education Global Practice. 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 ahasan1@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
change. However, in the case of the project evaluated in this paper, even a larger quantitative sample would probably have not helped.

This raises the broader question of whether such interventions are worth the effort. Our answer would be – maybe – because the cost was a modest $200,000, if the intervention was allowed more time to have a sustainable impact. Looking forward, the literacy levels of these districts are rapidly improving and development interventions need to be cognizant of this 12. Complex interventions that build citizen capacity and improve the capacity of communities to mobilize and engage with government can help greatly in the context of improving literacy. However, they require a fundamentally different approach to development that requires a reliance on a sandwich between bottom-up and top-down efforts, and constant experimentation and learning by doing to be effective.

# <u>References</u>

Ananthpur, Kripa, “Rivalry or Synergy ? Formal and Informal Local Governance in Rural India,” Development and Change, 38(3), Pp: 401–421, 2007.

Ban, Radu, Saumitra Jha and Vijayendra Rao, “Who has voice in a deliberative democracy: Evidence from transcripts of village meetings in India,” Journal of Development Economics 99(2), Pp: 428-438, 2012 Banerjee, A.V., R. Banerji, E. Duflo, R. Glennerster, and S. Khemani, “Pitfalls of Participatory Programs: Evidence from a Randomized Experiments in Education in India,” American Economic Journal: Public Policy 2(1), Pp: 1-30, 2010 Bardhan, P and D. Mookherjee, “Political Clientalism and Capture: Theory and Evidence from West Bengal,” Working Paper, Dept of Economics, Univ. of California, Berkeley, 2011 Baiocchi, Gianpaolo, Patrick Heller, and Marcelo K. Silva, Bootstrapping Democracy: Transforming Local Governance and Civil Society in Brazil, Stanford University Press, Palo Alto, 2011 Barron, Patrick, Michael Woolcock and Rachel Diprose, Contesting Development: Participatory Projects and Local Conflict Dynamics in Indonesia, Yale University Press, New Haven, 2011 Besley, Tim, Rohini Pande, and Vijayendra Rao, “Participatory Democracy in Action: Survey Evidence from Rural India,” Journal of European Economic Association 3(203), Pp: 648-57, 2005

> 12 Literacy rates in Gulbarga jumped from 54 to 64 percent between 2001 and 2011, and from 49 to 60 percent in Raichur.  These gains came entirely from sharp improvements in literacy among younger cohorts.  The expectation is that literacy in these districts will be close to 80 percent by 2021.

27
**Table 3** – The role of risk perceptions

||Percepti<br>risk of|on of high<br>infection<br>Dependen|Willing t<br>t variable|o vaccinate|
|---|---|---|---|---|
||(1)|(2)|(3)|(4)|
|Stringency index|0.002*<br>|0.002*<br>|0.003**<br>|0.003**<br>|
||(0.001)|(0.001)|(0.001)|(0.001)|
|Stringency index X Perception of high risk of||||-0.000|
|infection||||(0.001)|
|Perception of high risk of infection|||0.089*** <br>|0.103*<br>|
||||(0.010)|(0.058)|
|Vaccination campaign dummy|-0.026|-0.028|0.096***|0.096***|
||(0.018)|(0.018)|(0.021)|(0.021)|
|Daily deaths per million (7 day avg)|0.010**|0.010**|-0.000|-0.000|
||(0.004)|(0.004)|(0.006)|(0.006)|
|Know positive case|0.148***|0.148***|0.065***|0.065***|
||(0.014)|(0.013)|(0.014)|(0.014)|
|_Mediating factors_|||||
|No. people out of 100 who will vaccinate||0.001*<br>|||
|||(0.000)|||
|trusts govt. health authorities||0.048***<br>(0.013)|||
|_Individual attributes_|||||
|male|-0.051***|-0.051***|0.080***|0.080***|
||(0.014)|(0.014)|(0.019)|(0.019)|
|urban|0.046***|0.047***|0.009|0.009|
||(0.012)|(0.012)|(0.013)|(0.013)|
|age 20-30|-0.173***|-0.167***|-0.105*|-0.105*|
||(0.055)<br>|(0.055)<br>|(0.059)<br>|(0.059)<br>|
|age 31-40|-0.108*|-0.102*|-0.135**|-0.135**|
||(0.052)|(0.053)|(0.061)|(0.061)|
|age 41-50|-0.089|-0.085|-0.103|-0.103|
||(0.053)|(0.053)|(0.062)|(0.062)|
|age 51-60|-0.098*|-0.096*|-0.101|-0.101|
||(0.050)|(0.051)|(0.058)|(0.058)|
|age 61-70|-0.093|-0.092|-0.057|-0.056|
||(0.054)|(0.056)|(0.056)|(0.056)|
|age 71-80|-0.091|-0.090|-0.023|-0.023|
||(0.059)|(0.061)|(0.055)|(0.055)|
|primary edu or less=1|-0.044|-0.046*|-0.037*|-0.037*|
||(0.027)|(0.026)|(0.020)|(0.020)|
|secondary edu=1|-0.007|-0.007|-0.022*|-0.022*|
||(0.013)|(0.013)|(0.011)|(0.011)|
|in good health|-0.079***|-0.082***|0.000|0.000|
||(0.010)|(0.010)|(0.008)|(0.008)|
|Constant|0.071|0.052|0.447***|0.439***|
||(0.069)|(0.078)|(0.084)|(0.097)|
|Observations|15237|15237|15237|15237|
|R-squared|0.199|0.202|0.067|0.067|

Standard errors in parentheses clustered at country level. All estimations include country and month fixed effects.

* p<0.05  ** p<0.01  *** p<0.001

22
# **2. Methodology**

Our analysis is based on previous studies investigating the determinants of growth in developing countries. We use an empirical growth model originally set up by Loayza et al. (2005) which was improved and updated by Brueckner (2013). These cross-country growth regression models were originally constructed to investigate growth in Latin America and the Caribbean (Araujo et al, 2014).

Such cross-country growth regressions may have their limitations, but their insights should not be neglected. We are well aware that cross-country growth regressions have their limitations. While some strands in the literature neglect them altogether, we at least view them as one possible approach to gain insights into the dynamics of growth (see also Durlauf, 2009), especially in a country like Ethiopia where data coverage is relatively scarce. Furthermore, our econometric approach tries to address the most conventional methodological issues that can arise in crosscountry growth regression exercises.

This approach avoids tweaked Ethiopia-specific results. Taking an existing cross-country regression model to analyze Ethiopia’s recent growth performance potentially runs the risk that Ethiopia-specific factors might not be well-reflected in the model. However, this is essentially our goal as setting up a new cross-country model for our purpose will be prone to model selection that produces the ‘best’ results for the specific case of Ethiopia. In essence, our approach helps address the following question: can we explain Ethiopia’s recent growth performance by factors also observed to influence growth in other countries? Or is the Ethiopian case a specific one? Even if one remains skeptical of cross-country growth regressions, a failure of the model to appropriately predict observed growth in Ethiopia would suggests that factors that correlate with growth in most countries cannot explain Ethiopia’s growth acceleration. On the other hand, a good predictive performance would imply that Ethiopia’s growth acceleration is in line with experiences of other countries and allow us to decompose those correlates of growth in more detail.

## **2.1 Model and Data**

The underlying model expresses domestic income as function of key growth drivers. Our goal is to estimate the impact of certain variables _Xct_ on domestic income, measured as the natural log of real PPP GDP per capita ( _lnyct_ for country _c_ in period _t_ ). More formally, the estimated equation can be written as the dynamic (‘steady-state’) process: where _ac_ and _bt_ are country and time fixed effects, respectively; and _ect_ is an error term that remains unexplained by the model (‘residual’, i.e. the difference between predicted and observed growth). Note that a time period _t_ is the average over (non-overlapping) 5-year periods to smoothen shortrun and cyclical effects.

These drivers of growth are grouped into the categories of structural, stabilization, and external effects. Following the above-mentioned studies, the individual variables in the vector _Xct_ are assigned to those three categories. This facilitates an interpretation whether growth was driven by 6
elected head of the village, schools, Anganwadis, masons, and doctors (if available). Since our study sample was restricted to households with children < 24 months at enrollment, in the follow-up survey we added a rapid assessment from a random sample of households in the villages to measure sanitation coverage, quality of toilet construction, availability of hand washing place, type of drinking water source, and waste management practices.

**Block Questionnaire:** In each administrative block we conducted a survey to assess the inputs in TSC program in terms of finance, material, manpower and their associated cost. The purpose of this questionnaire was to conduct a detailed cost benefit analysis at a later stage (not included in this report) and to obtain official records of program implementation and status.

# **3.4  Field Implementation**

Protocols and instruments used for data collection were designed by the WSP global impact evaluation team. These were revised, adapted, translated, and piloted by the India principal investigators. All data collection activities were conducted in Hindi. Study protocols and instruments are available from the corresponding author upon request. GfK Mode, Ltd. was contracted to conduct the fieldwork. The baseline survey was conducted between May and July, 2009, and the follow-up survey was conducted between February and April, 2011. The follow-up survey was conducted in a slightly different season due to concerns that the TSC program would soon expand into control villages. The India principal investigators, global team experts and GfK Mode researchers trained the field teams. Six field teams, each with four interviewers, 2 anthropometrists, 1 microbiology sampler, 2 supervisors, and one editor conducted the fieldwork at follow-up. Two field executives and one field coordinator handled oversight of the work in Madhya Pradesh.

# **3.5  Statistical Analysis**

We compared the baseline characteristics of the randomized treatment groups to determine if any observed characteristics were imbalanced by chance despite randomization. Due to highly comparable groups at baseline and the large increase in our within-cluster sample between baseline and follow-up, our analysis focused on group comparisons post-intervention (using follow-up measures only). To evaluate the potential for attrition (loss to follow-up) between baseline and follow-up to bias our estimates, we compared baseline characteristics of those present at follow-up with those lost to follow-up; we also compared the balance of baseline characteristics across treatment groups for individuals who were present at both baseline and follow-up to determine whether attrition was differential by treatment group.

Our parameter of interest for all outcomes was the mean difference between randomized groups and we conducted the analysis using individuals as they were randomized (Intention to Treat; ITT). We estimated differences between groups using the following linear regression model: 10 / 41
regionally harmonize and upgrade their standards for the selected product at once, equating the regional standard to the international standard. This approach is followed by RTAs like the Association of South-East Asian Nations (ASEAN), The second approach is the _gradual upgrading approach_ : member countries upgrade their standards gradually towards the international standard rather than immediately. This approach tends to be followed by RTAs with members that have a technological level or health, security and environment objectives that are not aligned with international standards. Such is the case of the Andean Community and Mercosur. In order to guarantee market access as standards rise, member countries coordinate their upgrading by regionally harmonizing their standards towards a certain intermediate level. Exports satisfying this intermediate standards level are guaranteed market access to member countries’ markets.

To date, RTAs in the developing world have not begun to realize their full potential for overcoming standards related obstacles to regional or global trade. Though there is yet no clear best practice, it is possible to draw some common principles from RTAs’ past experiences and from existing literature for a more effective upgrading and harmonizing process of standards and conformity assessment procedures: prioritize sectors for reform; build trust between RTA members; set a quality regulation based on simplification, transparency and dynamism; allow for gradual reform if needed; build regulatory capacity; and promote mutual recognition of conformity assessment procedures.

This paper aims to contribute to the scarce literature on regional approaches to standards upgrading. It complements Kotschwar’s (2001) review of standards in Latin American RTAs and Xiaoyang-Chen and Mattoo’s (2004) assessment of the impact of regional standards agreements on trade by employing information obtained through interviews to draw lessons from RTAs’ experiences on standards upgrading. The interviews were conducted with representatives of firms, business associations, laboratories, accreditation bodies, standardization bodies, and national and regional bodies of TBT and SPS standards in Argentina, Brazil, Chile, Peru, Uruguay, and Washington DC.

The paper is structured as follows. Section 1 briefly presents standards and conformity assessment procedures. Section 2 reviews the unilateral and coordinated approaches to standards upgrading. Section 3 examines RTA standards upgrading and harmonizing experiences and derives some common features. Section 4 presents principles that can guide developing countries in the process of regional upgrading and harmonizing of standards and conformity assessment procedures and suggestions for a more effective participation in the international standards arena. The last section concludes.

# **1 STANDARDS, CONFORMITY ASSESSMENT AND DEVELOPING COUNTRIES**

A standard outlines the special characteristics of processes, products, or services. Standards facilitate trade since they “stipulate what can or cannot be exchanged and define the procedures that must be followed for exchange to take place” (Brenton 3