rafmacalaba/datause-encoder-data huggingface dataset:
# **B Appendix: Robustness check on cutoff age to restrict the sample**

Table B1: Robustness check using the sample of the aged 60 and below—Job search

|||Log(searc|h spell)|||Log(no. ap|plications)||
|---|---|---|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|
|Social networks|-0.465<sup>_∗∗∗_</sup>|-0.274<sup>_∗∗∗_</sup>|-0.229<sup>_∗∗_</sup>|-0.225<sup>_∗∗_</sup>|-0.452<sup>_∗∗∗_</sup>|-0.242<sup>_∗∗_</sup>|-0.226<sup>_∗∗_</sup>|-0.187<sup>_∗_</sup>|
||(0.087)|(0.105)|(0.099)|(0.093)|(0.098)|(0.093)|(0.089)|(0.105)|
|Schooing in years||0.065<sup>_∗∗∗_</sup>|0.038<sup>_∗∗∗_</sup>|0.018||0.048<sup>_∗∗∗_</sup>|0.026<sup>_∗∗∗_</sup>|0.027<sup>_∗∗_</sup>|
|||(0.011)|(0.010)|(0.013)||(0.012)|(0.008)|(0.011)|
|Age at hire||-0.009|-0.003|-0.004||0.007<sup>_∗∗_</sup>|0.010<sup>_∗∗∗_</sup>|0.008<sup>_∗∗_</sup>|
|||(0.006)|(0.006)|(0.006)||(0.004)|(0.003)|(0.004)|
|Father’s pri.school||0.034|0.130<sup>_∗_</sup>|0.150<sup>_∗∗_</sup>||0.039|0.089|0.062|
|||(0.079)|(0.078)|(0.073)||(0.064)|(0.060)|(0.067)|
|Mother’s pri.school||0.026|0.103<sup>_∗_</sup>|0.029||0.023|0.129<sup>_∗∗_</sup>|0.141<sup>_∗∗_</sup>|
|||(0.066)|(0.060)|(0.049)||(0.056)|(0.054)|(0.062)|
|Math z-score||0.005|0.012|-0.014||0.036|0.021|0.014|
|||(0.034)|(0.033)|(0.042)||(0.040)|(0.032)|(0.038)|
|Language z-score||-0.101<sup>_∗∗_</sup>|-0.086<sup>_∗_</sup>|-0.058||0.007|-0.006|-0.029|
|||(0.041)|(0.048)|(0.050)||(0.054)|(0.053)|(0.059)|
|Big 5 index z-score||0.001|0.144|0.081||-0.064|-0.113<sup>_∗∗_</sup>|-0.135<sup>_∗∗∗_</sup>|
|||(0.087)|(0.107)|(0.121)||(0.049)|(0.046)|(0.050)|
|Firm fxed efect|||X||||X||
|Firm-occ fxed efect||||X||||X|
|R-squared|0.166|0.223|0.147|0.108|0.115|0.182|0.131|0.094|
|N|3763|3757|3757|3757|3763|3757|3757|3757|

_Note_ . The variable, _Social networks_ , is the dummy indicating that social networks were used to find jobs. The other controls included are entry year fixed effects and geographical division fixed effects. Standard errors clustered within an establishment are in parentheses. Significance levels: _∗∗∗_ = 1%, _∗∗_ = 5%, _∗_ = 10%.

45
expectancy, average education levels and per capita income. The gini coefficients are based on recent surveys of income distribution.

The quality of a government's economic management is assessed through performance indicators of fiscal policy (debt-GDP ratio), monetary policy (central bank independence) and trade policy (outward orientation). For monetary and trade policy, we were able to use indices which capture, to some degree, the institutional orientation of government. The central bank independence index is based on the legally stated independence of the central bank. The outward orientation index includes a component of investors' perceptions of the receptivity of a government to trade. Unfortunately, the fiscal policy indlex, debt-GDP ratio, is a particularly imperfect measure of institutional orientation. This limitation is offset to some degree by the historical perspective it provides since debt is a cumulative measure of a country's fiscal policies. The indices of fiscal and monetary policy may be subject to a bias against poor countries. It is possible, for example, that the debt-GDP ratio may be biased against countries that are growing rapidly, regardless of the quality of their economic management since public investment typically has very long term payoffs. Or, conceivably, a country with a poorly developed revenue collection system may find monetization of debt to be the most efficient form of financing. However, neither of these indices are strongly correlated with income, suggesting that bias, if it exists, is not strong.

A more general question regarding bias is whether aggregating these indices introduces a systematic bias towards or against any country or group of countries. For example, does the better availability of data from developed countries mean that these countries, as a group, are rated higher or lower than LDCs? Or, does the composition of these indices by western oriented academics, businessmen and economists lead to a bias against governments pursuing alternative goals? The answer to the first question is that it seems unlikely. The answer to the second question is, yes, although ideological differences are more likely to develop over the weights applied to each objective rather than which objectives should be included. The index is flexible enough that adjustments could easily _5_
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# **Figures and Tables**

Figure 1: General Business Functions and Their Technologies <!-- Start of picture text --> Handwritten<br>processes<br><!-- End of picture text --> <!-- Start of picture text --> Computers with<br>standard software<br>(e.g. Excel)<br><!-- End of picture text --> <!-- Start of picture text --> Mobile Apps or Digital<br>platforms<br><!-- End of picture text --> <!-- Start of picture text --> Computers with<br>specialized installed<br>software<br><!-- End of picture text --> <!-- Start of picture text --> Enterprise Resource<br>Planning (ERP) or<br>equivalent software<br>integrated with other<br>back office functions<br><!-- End of picture text --> <!-- Start of picture text --> 2. Production or 4. Marketing/<br>service operations 3. Sourcing andProcurement Costumer 5. Sales 6. Paymentmethods 7. Qualitycontrol<br>planning information<br>Manual search<br>Handwritten of suppliers, Informal chat Direct sales at the Exchange of Manual,<br>processes without (face-to-face) establishment Goods visual or<br>centralized written<br>database. processes<br>standard softwareComputers with Computers with softwarestandard WhatsApp or Online chat Internet)(e.g. phone or e-mailDirect sales by Cash technologieswithout the support of digital<br>Cheque,<br>digital platformsMobile Apps or Online social media, Structured costumer surveys platforms or appsSales through social media voucher or bank wire visual or Manual, written<br>specialized Apps processes<br>Specialized software or digital Costumer Online sales using Prepaid, credit with the<br>for demand planning, Enterprise Resource demand forecast platforms Supplier Relation Relationship Managemensoftwaret (CRM) external digital Amazon, eBay, platforms (e.g.Alibaba) or debit card electronic Online or technologiessupport of digital<br>Planning (ERP) or Management payment Statistical<br>back office functionsintegrated with other equivalent software integrated with production (SRM) not analytics / Artificial Big data commerce) using Online sales (e-its own website Online process control<br>planning intelligence through<br>platform<br>Supplier Electronic orders<br>Relation integrated to Automated<br>Management specialized supply Virtual or systems for<br>(SRM) chain management cryptocurrency inspection<br>integrated with systems<br>production<br>planning<br><!-- End of picture text --> 39
# ALLOCATION AND NANAGENENT OF PUBLIC SPENDING

**23.** It **Is** worth paying attention too to the way in which budgetary aggregates are summarised, since this can affect the terms of debate on budgetary policy. A key concern should be the size of the budget **deficit** (defined as the gap between expenditure and domestic revenue) and there should be special attention to how the deficit will<sup>be financed (by</sup> external **aid** and by foreign and domestic borrowing). This essential information is often obscured by arbitrary classifications of revenue (e.g. by treating domestic borrowing as revenue on a par with tax receipts) and, most seriously, by a failure to present reasonable forward projections of the budget. It **Is** not just a question of **failing** to present this information publicly: all too often the planners themselves do not compile It or see the need for it.l51

# **Budget Hethodology -** tile **Importance of Seguence**

**24.** In principle, the determination of the budget Involves the solution of a set of simultaneous equations that reconcile revenues with expenditures and so forth. In practice, the process of formulating a budget **Is** as much political as it is technical or economic, and it is bound to be iterative. Whether the outcome of the process represents a sustainable budget path and whether the allocation of<sup>resources</sup> is optimal, subject to the general constraints on overall resource availability and other specific constraints that may apply, may well depend on the sequence the process follows.

25. A key aspect of the approach advocated in the present paper **Is** that it Involves looking at the entire set of public expenditure issues simultaneously. A system that allowo major expenditure decisions to be taken separately and at different times Is bound to generate an upward pressure on expenditures and Is very unlikely to achieve a satisfactory overall pattern of expenditure.C61 If total expenditure is not explicitly targeted, but allowed to be the outcome of a process of aggregation of sectoral bids, the aggregate expenditure target that emerges Is virtually

- 151 A similar sloppiness Is often shown in studies of public expenditure when the allocation of resources among sectors is analysed without making a distinction between discretionary and non-discretionary elements of expenditure. The biggest non-dlscretionary Item **Is** usually debt-service, and analyses of expenditure that do not separate out public debt can be particularly misleading. A sector's share of discretionary expenditure may have held up even when its share of total expenditure has fallen sharply.

- [61 But viewing the entire set of public expenditure options simultaneously means that there has to be direct competition among projects/programmes that may be at different stages of definitlon and appraisal. This creates methodological problems that are discussed later in this paper.

Page 14
Table 1. Duration and amplitude of rapid debt accumulation episodes Duration

|||Number o|f episodes,|by duration (|years)||
|---|---|---|---|---|---|---|
||Assoc|iated with cr|ises||No crises||
|Years:|2-4|5-10|11-|2-4|5-10|11-|
|Government debt|41|59|37|27|74|18|
|Private debt|27|39|39|37|83|38|
|Total debt|31|40|35|29|78|24|

# Amplitude

||A|Number<br>ssociated|of episodes,<br>with crises|by amplitud|e (percenta|ge points of<br>No cr|GDP)<br>ises||
|---|---|---|---|---|---|---|---|---|
|Percentage points of GDP:|-20|20-40|40-60|60-|-20|20-40|40-60|60-|
|Government debt|24|41|24|48|53|40|16|10|
|Private debt|66|17|13|9|97|48|11|2|
|Total debt|9|32|26|39|33|57|20|21|

Note: Total debt refers to the sum of government debt and private debt. A period of debt accumulation is identified with the algorithm in Harding and Pagan (2002). When a change in debt-to-GDP ratios over an accumulation period is above the maximum of 10-year moving standard deviation of the ratios during the period, it is considered as a rapid debt accumulation. The duration of episodes refers to the number of years from trough to peak debt-to-GDP ratios. The amplitude refers to the size of the increase in debt-to-GDP ratios over the same period.

24
Policy Research Working Paper 7835

# **Abstract**

Creating productive jobs is one of the greatest challenges in Ghana. This paper looks at job creation and its relationship with firm productivity and the quality of jobs among registered firms in the Ghanaian private sector, based on the 2013 World Bank Enterprise Survey. The study looks at the typology of firms in the industry and service sectors, identifying those that have created the most jobs, and the relative quality of these jobs in terms of productivity and firms’ average wage bill. Although the formal private sector employs only a tiny share of total employment, the results show that larger and older firms account for the majority of workers, and formal jobs density is highest in Accra (Accra Metropolitan Area and Tema). Large firms also pay higher wages on average, are more productive, and account for most of the aggregate net formal job creation between 2010 and 2012. However, the relationship between size and productivity is positive and statistically significant, mostly driven by the upper part of the firm size distribution, pointing to potential market segmentations as micro, small, and medium firms create fewer jobs and are less productive. Removing barriers to the growth of micro, small, and medium size enterprises, and to the allocation of resources toward more efficient firms should be a key priority for policy makers.

This paper is a product of the Social Protection and Labor Global Practice Group. 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://econ.worldbank.org. The authors may be contacted at dfrancis@worldbank.org and mhonorati@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
attempting to do any of these things in order to reduce or eliminate medium to long term costs (Sonderholm 2009d:312).

The second objection is misguided (and ironic) given that the very core of the welfarist position is the idea that the morally right course of action, institution or policy is the one that maximizes future human welfare (that is, minimizes future human ill-fare). The consistent welfarist is moved by the scale of human suffering in low-income countries due to the combination of disease and the access and availability problems (together with a host of other social, economic and cultural factors). But she is also moved by future human suffering caused by existing and new diseases, and it is because she is not prepared to prioritize the alleviation of current human suffering over the alleviation of greater, future human suffering that she is opposed to the abrogation of IPRs for drugs.

The second objection, moreover, assumes that the only way of making drugs available to those low-income populations that need them is by abrogating IPRs for such drugs. This assumption is, however, false. It is a fallacy of false alternatives to suggest that either IPRs for such are abrogated or such drugs cannot be made available to those who need them. There are alternative ways of making such drugs available to those who need them and thereby ease the access problem and the suffering that accompanies it. Trade barriers that make it impossible for developing countries to sell their products in the developed world could be eradicated. Such a move will most likely lead to a dramatic increase in the earnings of developing countries, and given that these countries are prepared to spend some, if not all, of these earnings on the welfare of their citizens, there would be a significant amount of resources available for the purchase of relevant drugs (Sonderholm 2009d:312).<sup>31</sup>

> 31 (Attaran 2004:163) adds some perspective to this line of thought. Data from the OECD (2002) suggests that US$

> 310 billion is spent on agricultural subsidies by Asian, European, and North American governments. According to

39
period, resources were reallocated to manufacturing activities with high productivity growth in Africa. Structural change stalled in the mid-1970s. When it resumed in the 1990s, workers mainly relocated to distributive trade services. Productivity levels in these activities were higher than in agriculture, enhancing overall economy performance. But services productivity growth was sluggish and increasingly falling behind the world frontier. This pattern of static gains but dynamic losses of reallocation since 1990 is found for many African countries. It is comparable to patterns observed in Latin America, but different from those in Asia.

Along the same vein, Diao _et al_ . (2017) also find that in contrast to the East Asian experience, none of the recent growth accelerations in Latin America, Africa, or South Asia was driven by rapid industrialization. Beyond that, these authors document that recent growth accelerations were based on either rapid within-sector labor productivity growth (Latin America) or growth increasing structural change (Africa), but rarely both at the same time. The African experience is particularly intriguing, as growth-enhancing structural change appears to have come typically at the expense of declining labor productivity growth in the more modern sectors of the economy. The paper explains this anomaly by arguing that the forces that promoted structural change in Africa originated on the demand side, through either external transfers or increase in agricultural incomes. In contrast to Asia, structural change was the result of increased demand for goods and services produced in the modern sectors of the economy rather than productivity improvements in these sectors.

Mallick (2017) also highlights the importance of demand factors for structural change in Asian countries. This author examines the sources of structural change and its contribution to labor productivity growth in China and India in the context of globalization. He found that changing final demand is the most crucial factor in labor reallocation in India. In China, both changes in final demand and technology are the driving factors of labor allocation. The regression analysis confirms that structural change, globalization, and human capital significantly contribute to labor productivity growth in both countries.

Grabowski and Self (2019) have also examined the experience of structural change in Asian countries. Using data over the period 1985-2015, covering four Southeast Asian countries 6
occur to other farmers in China. An important caveat, however, is that our analysis assumes that there will be no change in water supply. However, it is likely that with at least some climate scenarios, water supplies will be reduced which could lead to large losses. The effect of water needs to be incorporated in future studies.

It is also quite apparent that the effects of climate change are not going to be uniform across the country. Warming will assist areas that are currently very highly productive and will further handicap areas that have below average productivity. In particular, warming will help the southeast region but hurt the west and far north. Chinese policy makers need to be aware that warming is likely to impose additional costs on specific regions that already have below average incomes.

The fact that the crop studies predict much larger damages than the Ricardian studies suggests that adaptation matters. The ability of Chinese farmers to change and adapt to new conditions has allowed China to outperform other agricultural economies in the world and will continue to be important with respect to climate change. However, for farmers to be able to endure future climate changes, it is critical that policies allow them to get the most out of the available factors of production and natural resources. The results of this study suggest that the direct effect of temperature rise and precipitation change on farms may not be a great risk to China in the near future. However, the effect of climate change on water is likely to be quite important. Given that water is already a very critical resource in certain regions of China, policy makers may want to use this resource wisely, especially in regions where water is scarce. Climate change increases the pressure to develop institutions and infrastructure in water scarce regions to treat water as a valuable resource. Although uniform national policies have many desirable properties, when it comes to water, it is critical to develop efficient policies in the water scarce regions.

In order to address future warming, China may also consider developing management practices and new varieties (crops and livestock) for a warmer world. Finally, China would benefit from adaptation at large, by having new technologies (research), educating farmers about better technologies (extension), and building credit institutions to allow farmers to purchase and apply needed technology.

17
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