rafmacalaba/data-use-mentions-extended huggingface dataset:
is the subjective nature of the innovation measurement, we examine the extent to which the different types of bias that occur when collecting subjective data play a role in innovation measurement.

Results show that in many cases self‐reported innovations in the short and long questionnaire are different, even when the same person is interviewed in the two waves or when explanatory cards with examples or definitions to improve the comprehension of the innovation questions are shown. More importantly, for self‐reported innovations that can be verified we find that the short questionnaire provides an incorrect answer in a significant number of cases. We find that issues of framing explain some of this unreliability, while cognitive problems do not appear to play a significant role. Overall, we found that some of the questions by which innovation is measured in current surveys are not appropriately designed to measure innovation in developing countries. This is especially important when using short surveys and, therefore, we recommend not to use short innovation modules with only a few questions in firm‐level questionnaires that do not provide detailed verification questions.

The paper makes several contributions to the discussion on how to measure innovation. First, to the best of our knowledge this is the first paper that builds on the literature on subjective data to empirically analyze the potential sources of bias that may affect respondents’ behavior in innovation surveys. Second, the paper makes use of a unique effort conducted by the World Bank Group to increase the coverage of innovation surveys. The data used are the most comprehensive set of comparable cross‐country surveys on innovation in developing countries available so far. Finally, the paper reports on a unique experiment carried out to analyze methodological issues affecting data collection efforts and to assess the robustness of the Oslo manual framework in the context of developing countries.

The paper is structured as follows. The next section discusses the conceptual framework for the analysis. Section 3 presents the data used and the experiment conducted in data collection. Section 4 describes the extent of firm level innovation in the two surveys and analyzes
# **Annex Table 6: Development Drivers of the Non-Life Insurance Industry**

## **Annex Table 6: Development Drivers of the Non-Life Insurance Industry (Source: Feyen, Lester, and Rocha (2010))**

The dependent variable is the logarithm of the volume of non-life insurance premiums as a fraction of GDP. The sample consists of annual data for the period 2000-08. All regressions are estimated using pooled Ordinary Least Squares. Year-fixed effects and a constant were estimated but are not reported. LSCHOOLING, LLIFE_EXP, LINCOMETOP20, and LCONTRIB_RATE are sample period averages. In all regressions, White‟s heteroskedasticity-consistent <u>(clustered) t-values are given in parentheses (brackets). ***, ** and * represent significance at 1, 5 and 10% level respectively.</u>

|VARIABLES|1|2|3|4|5|6|
|---|---|---|---|---|---|---|
|LGDPPC|0.14|0.26|0.30|0.20|-0.056|0.20|
||(3.48)***|(18.4)***|(14.6)***|(10.1)***|(-0.46)|(7.84)***|
||[1.81]*|[6.61]***|[7.26]***|[3.59]***|[-0.38]|[3.91]***|
|LPOP|-0.0017|-0.035|-0.073|-0.034|-0.020|-0.069|
||(-0.081)|(-3.40)
_n_ 2 where _hri_ = ∑ _j_ =1 _zij_ is the Herfindahl index for industry _i_ in region _r_ and is calculated as the sum of squared firm shares of local industry employment and _eri_ is industry _i_ ’s employment in city _r_ . Multiplying raw industry employment by (1− _hri_ ) has the desired effect of penalizing regions that have “lumpy” industry employment, that is, few firms with many workers.

To illustrate the importance of controlling for firm-size distribution in the measurement of localization potential, let us consider the following two-region example. Total single industry employment in Region 1 is 200, distributed evenly across 10 firms. In this case, the Herfindahl index is 0.1 and adjusted employment<sup>e~</sup> i1<sup>is 180. The</sup> adjusted employment showing localization potential is nearly the same as pure employment, reflecting the considerable possibility for firm interaction. In comparison, total industry employment in Region 2 is also 200, but distributed between two firms, with the first firm having 180 employees and the other firm with 20 employees. In this case, the Herfindahl is 0.82, and the adjusted employment<sup>e~</sup> 2i<sup>is 36. This example shows</sup> that a fewer number of firms and ‘lumpy’ employment in one firm reduces the overall potential for localization economies. Thus, our measure<sup>~</sup> eri penalizes regions where employment is concentrated in a few firms. For the analysis, we calculate own industry concentration using employment and firm-size distribution statistics provided in the 1998–99 sampling frame of the ASI, which provides employment data on the universe of registered industrial establishments in India.

16
>to 1977<br>Prices<br>for<br>Gross<br>Output|
|---|---|
|2041 Flour and Other Grain Mill Products 4,327.6<br>3,412.0<br>2046 Wet Corn Milling<br>2,141.7<br>1,548.6|126.8341<br>138.3022|
|TOTAL<br>6,469.3<br>4,960.6|130.4141|

Source: Gross Value of Output at 1975 US$ from US Dept. of Commerce. Annual Survey of Manufactures.
- Brubaker, J., Kilic, T., and Wollburg, P. (2021). Representativeness of individual-level data in covid-19 phone surveys.

- Cocco, M. and Tuzzi, A. (2013). New data collection modes for surveys: a comparative analysis of the influence of survey mode on question-wording effects. _Quality & quantity_ , 47(6):3135–3152.

- Cullen, C. (2020). Method matters: Underreporting of intimate partner violence in nigeria and rwanda. _World Bank Policy Research Working Paper_ , (9274).

- Cullen, W., Gulati, G., and Kelly, B. D. (2020). Mental health in the covid-19 pandemic. _QJM: An International Journal of Medicine_ , 113(5):311–312.

- Dabalen, A., Etang, A., Hoogeveen, J., Mushi, E., Schipper, Y., and von Engelhardt, J. (2016). _Mobile phone panel surveys in developing countries: a practical guide for microdata collection_ . World Bank Publications.

- De Weerdt, J., Beegle, K., Friedman, J., and Gibson, J. (2016). The challenge of measuring hunger through survey. _Economic Development and Cultural Change_ , 64(4):727–758.

- De Weerdt, J., Gibson, J., and Beegle, K. (2020). What can we learn from experimenting with survey methods? _Annual Review of Resource Economics_ , 12:431–447.

- Demombynes, G., Gubbins, P., and Romeo, A. (2013). Challenges and opportunities of mobile phone-based data collection: Evidence from south sudan. _World Bank Policy Research Working Paper_ , (6321).

- Dillon, B. (2012). Using mobile phones to collect panel data in developing countries. _Journal of international development_ , 24(4):518–527.

- Ding,
in Table 5.2. To understand how to interpret it, take the example of Row (1), which examines the simple quantitybased years-of-schooling measure. Row (1) shows that the average years of schooling of 25- to 29-year-olds in the four lowest-performing countries (in this sample) is 7.1, compared with 14.2 among the four highest-performing countries; the global “gap” as measured by the ratio of best to worst performers is therefore 2.0. If one were to just look at scores on the TIMSS 2015 Math assessment, the gap would be 1.6. Unsurprisingly, the approaches that combine quantity and 40
developed by Galster et al. (2001) was adopted.<sup>59</sup> This Centrality Index (CI), measures the average distance of the population from the city center, normalized by the total area of the city. This measurement is slightly different than the density gradient, in that it is not influenced by the city’s size, and therefore better suited to compare cities of different sizes. <mark>Figure X</mark> shows Nairobi and Addis having a higher level of centrality than Kigali, suggesting that Kigali is more compact and has a larger proportion of its population living close to the city center. Nairobi and Addis, on the other hand, have a slightly more polycentric population distribution. Decentralization of urban areas is often cited as a cause for longer travel distances or times and inefficiencies of land use. CI helps to understand the extent to which the urban area is characterized by a monocentric form as opposed to a polycentric form.

<!-- Start of picture text --> Figure A1: Centrality Index<br>Centrality Index<br>0.06<br>0.05<br>0.04<br>0.03<br>0.02<br>0.01<br>0<br>Addis Ababa Nairobi Dar es Salaam Kigali<br>Note: Less sprawling cities have lower CI values.<br>Data Source: Landscan 2012 and GHSL 2014. Calculations made by Author<br><!-- End of picture text -->

# **Clustering**

Building upon the notion of compactness, the study turns to measure the spatial clustering of land cover. Interested in understanding how disperse or clustered each land cover type was, a global Moran’s I statistic was generated for Industrial/Commercial, Residential Regular, and Residential Irregular. Moran’s I measures the spatial autocorrelation of features based on their location, in other words, the degree to which
<!-- Start of picture text --> Figure 8. Output informality and underdevelopment<br>A. Informality and GDP per capita (2019) B. Informality, labor productivity, and human<br>capital<br>10,000 2017 PPP $ / Year<br>EMDE (in blue) 12 EMDEs with below-median informality<br>EMDEs with above median informality<br>10<br>Indonesia 8<br>6<br>AEs (in red) 4<br>2<br>6 8 10 12 0<br>Ln GDP per capita Labor productivity Years of schooling<br>60<br>50<br>40<br>30<br>20<br>10<br>MIMIC-based output informality (% GDP)<br><!-- End of picture text --> Sources: World Bank World Development Indicators, Elgin, et al. (2021 updated), and World Bank Staff estimates. A. Informality is captured by MIMIC-based informal output as a share of GDP. B. The sample is constrained to EMDEs, and data are averaged over 2011-19 to avoid the impact of the global recession around 2020 and 2008/09. EMDEs are grouped into “above-median” and “below-median” self-employment as a share of total employment.

33. **The link between informality and underdevelopment is supported by evidence in Indonesia.** First, output informality in Indonesia is most prevalent in the agriculture sector, followed by labor-intensive low-value-added service sectors (such as wholesale, retail, and hospitality sectors). Informal output in the agriculture sector is almost double the share of total informal output in the economy. It has declined slightly compared to its level in 2001 (figure 9). Wholesale, retail trade and hospitality sectors also pose a relatively larger share of informal output compared to other sectors though the share declined significantly compared to 2001. This is similar to a broad informality trend in other countries where
All households Assumed co-located with household location Housing

# **_3.3.1 Accessibility analysis_**

The accessibility of certain infrastructure services (education, hospitals, and health facilities) is modeled by connecting all households via the road network to the closest infrastructure asset. This is done by first creating a topologically correct road network using the road infrastructure data. Second, based on the road type ( _e.g._ , highways or zila road) and paving ( _e.g._ pucca or katcha), we assign a speed to the road segment. The processed road map with allocated speeds is shown in Figure E1. Third, we assign every household location in the synthetic household survey to the closest road and every infrastructure asset to the closest road. Then, for every household, we find the closest asset that this household can reach and derive the time and distance it takes to access these assets. Based on this, we find the total number of households that are using each individual asset and the road segments that are used to reach this asset.

For electricity services, we connect the urban households with electricity access to the closest substation, assuming that they will be connected to the substation via a local distribution network. We assume that rural households are not connected to the main grid, but instead use rural community electricity services, such as solar panels. As described in Section 3.2, we assume that tube wells and pit latrines are co-located with households, and the infrastructure service provision is directly modeled using the location of households in the SHSD data.

# **_3.3.2 Infrastructure services_**

Using the accessibility analysis, we can derive the system of infrastructure services across the coastal zone. Across the coastal zone, 71% of the urban households have access to electricity. Moreover, 88% of the rural households and 75% of the urban households are using dug wells for accessing drinking water, which, given a total of around 0.5 million functioning
29.1|33.6|28.8|29.3|
|Agriculture, forest & fishery|0.0|0.0|0.0|0.0|0.3|0.4|
|Government & Others|0.4|2.9|0.3|2.7|0.6|4.5|
|Total %|100.0|100.0|100.0|100.0|100.0|100.0|
|TotalNo. (in 1,000)|587|7,135|725|8,609|6,350|60,158|

Source: Statistics Bureau, _Jigyosho.kigyo tokei chosa houkoku_ (Survey on Business Establishments and Enterprises in 2001). Tokyo. 2002.

Table 4: Industrial Districts of Tokyo: Ota and Sumida

||Ota|Sumida|Tokyo|Japan|
|---|---|---|---|---|
|Total no. of establishments|35,367|19,342|724,769|6,350,101|
|Total no. of jobs|327,584|167,811|8,608,794|60,158,044|
|Manufacturing establishments|7,117|5,658|79,374|650,950|
|(Percent share in the total establishments)|(20.1%)|(29.3%)|(10.9%)|(10.3%)|
|Manufacturing jobs|73,676|43,480|1,097,984|11,126,145|
|(Percent share in the total jobs)|(22.5%)|(25.9%)|(12.8%)|(18.5%)|
|Manufacturing establishments with|||||
|
sample because the dependent variables are all undefined for donor-recipient pairs with no aid transfers.

> 7 Larger donors at the global level do not always have higher average aid shares at the recipient level, as some donors concentrate their aid in fewer countries.  Portugal‟s average aid share (23.5%) exceeds that of the U.S. (12.4%), although the U.S. provided more than 100 times as much total aid to countries in the sample as Portugal. 8 This indicator is a composite of numerous corruption-related indicators collected from various sources including surveys and risk assessment firms.  It is similar in many respects to Transparency International‟s even more widely known Corruption Perceptions Index, but includes more data sources and covers more countries.

> 9 An index scored from 1 to 7 is available going back to 1972, but we use a more finely-grained version scored from 0-100 that is available for 2003 onward.  The political freedoms indicator produced by Freedom House includes

9
To produce comprehensive measures of the business environment, we supplement the WBES data with cross-country data on the political and business environment: telecommunications, infrastructure quality, the incidence of domestic conflicts, and political competition.

We address the potential endogeneity of the business environment in several ways.<sup>5</sup> First, we mainly rely on objective measures of the business environment. Subjective answers may be based on firms’ performance directly, and may be determined by country-specific factors such as exposure to the media and development history. Second, we do not directly use firms’ answers on the business environment. Instead, we rely on city-industry-size averages of firm answers to gauge the local business environment. This local measure is less subject to the reverse causality issue associated with firm-level answers, and may provide a better proxy for the actual business environment. Finally, to check for possible omitted variables, we control for additional local and country-level determinants of firm outcomes, and show that our key results remain robust. However, with observational data, it remains true that endogeneity issues—especially in the context of a horse race between various alternative explanations—can never be ignored. This is especially true when many conventional instruments proposed for a particular variable (such as institutions) are often correlated with other channels in the residual of the performance equation (Bazzi and Clemens 2010; Morck and Yeung 2011). We thus resort to as many robustness checks as possible, and offer a coherent story to tie various findings together (Rosenbaum 2010). We offer a menu of facts and explanations, and we invite readers to offer alternative explanations for what we find here.

> 5 S ee also Dollar et al. 2006, Aterido et al. forthcoming; Xu 2011

5
# 1. Introduction

This study analyzes poverty dynamics and economic mobility in Malaysia over the period 20042022. We make use of a synthetic panel based on nationally representative cross-sectional microdata to investigate the movements of Malaysian households across the income distribution. We take three perspectives: first, we study mobility at the lower end of the distribution by focusing on poverty dynamics. Second, we take a broader view of economic mobility by dividing the distribution into three groups and analyzing upward and downward mobility along those dimensions. Finally, we assess relative mobility by considering transitions across quintiles over the entire income spectrum.

analysis by including survey data on 2019 and 2022. Second, it takes an expanded view by explicitly analyzing various scenarios for setting the poverty line and for incorporating the concepts of vulnerability and economic security. Third, it gives the first estimates of relative mobility based on these microdata. Lastly, we introduce a methodological refinement such that we are able to present bootstrap point estimates for all transitions, whereas the previous study estimated upper and lower bounds on mobility only.

We conclude that the picture of economic mobility in Malaysia over the period 2004-2022 is generally positive, with large reductions in chronic poverty and a growing group that we classify as economically secure. However, these gains are not uniform and depend on how we define income groups, and on which population subgroup we consider. Chances of remaining poor and of falling into poverty are highest in rural East Malaysia. Moreover, attaining economic security through sustained upward mobility is particularly difficult in rural East Malaysia and for East Malaysia Bumiputeras, two groups that overlap to an important extent. Downward mobility seems to have increased for these groups. Lastly, relative mobility results show considerable persistence in the position of sizeable groups at either the bottom or the top of the distribution. Over our study period, we do not observe episodes of greater relative mobility – the ordering of Malaysian society as expressed through its income distribution did not exhibit major changes.

The paper proceeds by discussing methodology and data in the next section.
and firm productivity in that region.

Following Reyes et. al (2017), we use the World Bank Enterprise Survey data set. We distinguish three different classifications for business environment (BE): Basic BE, Refined BE, and Agglomeration Environment. Basic BE is likely essential for facilitating firm growth. It consists of Basic Protection (corruption, basic property rights protection, and basic physical safety), infrastructure (power supply and modern telecom), human capital, and access to finance (such as bank finance and trade credit). Refined BE covers other BE elements that have been frequently mentioned in the literature, but perhaps less frequently mentioned than Basic BE. It includes topics such as entry and exit, labor regulations, tax burdens. The Agglomeration Environment is

> 6 Petkova et al. (2013) provide an overview of available studies.

4
mechanism linking such policies to subsequent economic growth, relying primarily on the econometric evidence presented in Hausmann, Pritchett and Rodrik (2005).

# _C. Exchange Rates and FDI_

Another literature analyzes the link between exchange rates and FDI. One strand has focused on an empirical regularity, namely that FDI seems to rise during and after severe balance of payments crises. Krugman (2000) was perhaps the first to coin the term “fire-sale FDI” to describe this phenomenon, but several contemporary theoretical and empirical treatments have provided further support to this notion.<sup>6</sup> Blonigen (1997) advanced our understanding of the link between exchange rates and FDI by proposing a theoretical model in which FDI seeks to acquire “firm-specific” assets, and finds support in data on Japanese acquisitions of U.S. companies during 1975-1992. Aguiar and Gopinath (2005) further pursue the hypothesis that FDI in pursuit of mergers and acquisitions increased during liquidity crises (and devaluations) experienced by East Asia during 1996-1998 and concluded that this effect was particularly prominent in the tradables sector, thus suggesting that FDI might in fact be a stepping stone for the recovery of trade after such crises. World Bank observers have taken this literature seriously, and some have concluded that we can expect an uptick in FDI in the aftermath of the 2008-09 crisis (see, for example, Calderón and Didier 2009).

# _D. Vertical versus Horizontal FDI_

One of the most cited articles in the FDI literature is Carr et al. (2001), which introduced the terms “horizontal” and “vertical” multinational enterprises (MNEs). The former refers to MNEs with foreign affiliates that sell final goods in the host market, whereas vertical MNEs exploit international differences in factor endowments or relative factor costs to export final goods elsewhere. The original motivation for these authors was the emergence of the so-called “new trade theory,” which argued that economies of scale can explain the rise of intra-industry trade during the second half of the twentieth century.
- Rasul, I., & Rogger, D. (2018). Management of Bureaucrats and Public Service Delivery: Evidence from the Nigerian Civil Service. _The Economic Journal_ , _128_ (608), 413–446. 13

- Roelcke, G., Nkya, F. M., Besta, N. A., Mchallo, I., Musyangi, M. E., & Orao, S. (2018). Urban local government strengthening program united republic of tanzania (program-for-results operation): Quality assurance review of the sixth annual performance assessment (assessing the performance during fy 2016/17). 26

- Stern, N. H., Dethier, J.-J., & Rogers, F. H. (2005). _Growth and empowerment: making development happen_ . Cambridge, Mass.: MIT Press. OCLC: 62034045. 1

- Stewart, D. (1795). _Account of the Life and Writings of Adam Smith, LL.D._ . 1

- Tilly, C. (1992). _Coercion, capital, and European states, AD 990-1992_ . Studies in social discontinuity. Cambridge, MA: Blackwell, rev. pbk. ed ed. 4, 7

- Weber, M. (1946). _From Max Weber: Essays in sociology_ . New York: Oxford university press. Open Library ID: OL6498314M. 7

- Weigel, J. L. (2020). The Participation Dividend of Taxation: How Citizens in Congo Engage More with the State When it Tries to Tax Them. _The Quarterly Journal of Economics_ , _135_ (4), 1849–1903. Publisher: Oxford Academic. 4

- World Bank (2005). Project appraisal document on a proposed loan in the amount of us$14.50 million and a proposed credit in the amount of sdr 9.92 million to the republic of Indonesia for the initiatives for local governance reform project. 27

- World Bank (2011). _Conflict, security and development_
: Total exports and imports are constructed by aggregating over the firm-level custom’s data. The denominator in the ratios and the WDI deflator are constructed using series downloaded from the World Bank’s online World Development Indicators.

4 The average GNI per capita for all of sub-Saharan Africa, excluding a few high-income countries, was almost double, at 3,680 (current PPP) in 2017.

5 Only between 2014 and 2016 do the two deflators differ noticeably with the prices in the WDI deflator rising more rapidly than using the US deflator to adjust the trade values that are reported in USD.

4