rafmacalaba/datause-encoder-data huggingface dataset:
**Table 1. Commonalities of Commodity Prices**

|**Panel A: Uni**<br><br>|**formSpacings **<br>|**Analysis**<br>||
|---|---|---|---|
|<sup>ˆ</sup><br>_Num_<br>_correl_|_ber of small_<br>_ationpairings_|_Small svr_|_Large svr_|
|0.308|85|0.145|4.504*|
|**Panel B**<br>|**:PANIC Analy**<br>|**sis**<br>||
|Factor|Idiosyncratic|Info|rmation Criteria|
|||IC1|IC2<br>IC3|
|-0.003, 0.835, -1.660, -1.693, -2.698<br>[0.335,0.162,0.118,0.107,0.059]|1.310|5|5<br>1|

_Notes_ : Panel A presents evidence on the degree of cross sectional correlation. <sup>ˆ</sup> is the proportion of correlations that are small. Ng (2006) Spacings Variance Ratio test statistic ( _svr_ ) provides evidence of whether correlation is significantly different from zero, distributed as standard normal, therefore the critical value is 1.65 (significant at 5% with asterisk, *). First order serial correlation is removed following Ng (2006), suing an AR(1) approach. There are _n_ = _N_ ·( _N_ -1)/2 = 276 correlations, for _N_ = 24. Panel B examines the stationarity properties of our panel time series by examining the unit root of factor nonstationarity and idiosyncratic nonstationarity. We use annual data on commodity prices from 1900 to 2008 ( _N_ = 24, _T_ = 109). We identify the factor structure using an information criterion from Bai and Ng (2002). For the factor unit root test, we reject the null hypothesis of a unit root for large negative (less than -2.89) and for the idiosyncratic component we reject the null hypothesis of a unit root for large positive values of the test statistic

# _4.2 Uniform Spacings Analysis_

To assess the pervasiveness of co-movement in commodity prices, we first apply the Ng‟s (2006) Spacings Variance Ratio (SVR) test. This test partitions a series of linear relationships in a panel data set into subsamples of „small‟ and „large‟ correlations. The proportion of small correlations is represented by <sup>ˆ</sup> . If the SVR test statistic is significantly different from zero, pairings in a particular subsample are significantly correlated. If the small group correlations are significant, so must the subsample of pairings with large correlations. If only the subsample of large correlations is significant, then we have only a degree of correlation in the data.

We find evidence of a significant degree of correlation in our panel (see Panel A, Table 1). The SVR for the large group of correlations, which represent about 70% of the data (i.e. <sup>ˆ</sup> = 0.31), has a test statistic of 4.504, when the 5% critical value is 1.65, and hence allows us to reject the null hypothesis of no significant correlation in our 24 commodity price indexes. For the remaining 30% of correlations in the small 14
# **Table 2:** Fixed Effects Estimation

# Dependent Variable: STANDARD DEVIATIONS OF GDP, CONSUMPTION, AND INVESTMENT GROWTH

|||||(A|nnual Ra|tes)|||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
|||_GD_|_P_|||<br>|_C_||||||
||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|(9)|(10)|(11)|(12)|
|_BANKt-_<br>_1_|-8.18*<br>(2.89)|...|...|...|-9.30*<br>(3.02)|...|...|...|-9.97*<br>(4.82)||||
|_LLYt- 1_|_..._|8.40<br>(5.56)|...|...|...|ll.1*<br>(5.20)|...|...|...|9.92<br>(8.95)|...|_|
|_PRIVATEt-_<br>_1_||_|-2.31*<br>(.643)|...||...|-2.37*<br>(.662) _|...<br>|...|...|-1.32<br>(1.84)||
|_PRIVYt-_|...|...|...|-2.06<br>(2.74)|...|...|...|-. 968<br>(2.66)|...|...|...|4.96<br>(4.77)|
|_GROWTHt_|.219<br>(.212)|.174<br>(.216)|.193<br>(.216)|.170<br>(.220)|.330<br>(.310)|.234<br>(.319)|.280<br>(.311)|.252<br>(.316)|.083<br>(.123)|.117<br>(.122)|.084<br>(.122)|.098<br>(.116)|
|_MEANt-±_|.151<br>(.230)|.014<br>(.255)|-.008<br>(.250)|.003<br>(.240)|.237<br>(.404)|.066<br>(.429)|- .144<br>(.431)|-.052<br>(.410)|-. 246<br>(.588)|- .517<br>(.593)|-.559<br>(.571)|- .569<br>(.546)|
|_INFMEANt_|-.016|-.030|-.044|-.029|-.029|-.025|-.062|-.023|-.011|-.009|-.043|-.009|
||(.044)|(.045)|(.046)|(.045)|(.048)|(.049)|(.050)|(.049)|(.079)|(.081)|(.081)|(.080)|
|_INFSTDEVt_|.046<br>(.031)|.056**<br>(.032)|.067*<br>(.032)|.053**<br>(.032)|.074*<br>(.034)|.066**<br>(.034)|.099*<br>(.037)|.064**<br>(.034)|.049<br>(.076)|.043<br>(.079)|.076<br>(.079)|.043<br>(.078)|
|_FXVOLt_|10.8*<br>(4.73)|11.7*<br>(5.07)|13.0*<br> (5.12)|11.7*<br>(5.26)|9.20*<br>(4.10)|10.0*<br>(4.47)|12.0*<br>(4.43)|10.3*<br>(4.66)|17.9*<br>(6.73)|18.9*<br>(7.01)|20.1*<br>(7.07)|20.0*<br>(7.05)|
|_No. of obs._|198|192|197|198|199|192|198|198|198|191|197|197|
|_R2_|.56|.53|.55|.54|.62|.59|.61|.59|.68|.67|.68|.67|

Note: Colntry-specific and time-specific fixed effects estimate. Heteroskedasticity-corrected standard errors are in parentheses. *, ** respectively denote significance at the 5 percent and 10 percent levels. The variables _GOVMEAN, GOVSTDEV, POLITY, OPEN, OPEN * FXVOL_ are included but not shown.
more effective to give them access to a marketplace for business services where they can hire skilled specialists.

We test this idea through a randomized experiment in Nigeria, carried out as part of a government program intended to help small firms grow. We randomly assigned a sample of 753 firms (each with 2-15 workers) into a control group and four treatment groups. The first treatment group used the common approach of _training_ the entrepreneur, providing a mix of 25 hours online and 12 days in-class business training. The second treatment group used another approach that has been gaining popularity in which the government pays for business consultants to provide personalized _consulting_ to the entrepreneurs, with firms receiving 88 hours of support. The third and fourth treatments supported the entrepreneur to use an online marketplace for business services, with a declining subsidy over nine months. The _insourcing_ treatment group was linked to Human Resource (HR) service providers, who helped the entrepreneur recruit an accounting or marketing specialist to join her firm as a full-time employee (insourced worker). The _outsourcing_ treatment group was linked to Accounting and Marketing service providers, who could be contracted by the entrepreneur to carry out relevant business functions via their external specialists (outsourced professional). The training, insourcing and outsourcing treatments were designed to be of equivalent cost to the government, while the consulting treatment cost twice as much.

We carried out two rounds of follow-up surveys, at one and two years after the start of these interventions. This includes detailed measurement of 41 different business practices, representing both traditional activities (in finance/accounting, marketing/sales, operations/HR), and also more novel activities (in digital marketing). The training treatment does not have a significant impact on business practices, nor on firm growth. In contrast, the other three treatments result in statistically significant improvements on a range of business practices (including a physically verified subset) and these effects persist well over a year after the interventions ended. Most firms given the insourcing or outsourcing treatments chose to hire marketing specialists and, in line with this business support, we find the largest improvements occur in the areas of marketing and digital marketing practices. The insourcing and outsourcing interventions also result in an increase in product innovation activities and, two years after the intervention, the outsourcing treatment results in a statistically significant increase in profits and sales (0.23 s.d.). The estimated impacts on profits and sales are smaller and not statistically significant for insourcing (0.12 s.d.) and 3
third at the beginning of the 2000s. The lion’s share of the increase in cross-border M&A is explained by the privatization of state enterprises that took place during the 1990s in many developing countries. The share of cross-border M&A in FDI also increased markedly in industrial countries.

In that context, this paper set out to answer two questions. The first one is about the continuation of the FDI boom to developing countries; specifically, would it continue after the privatization process and the ensuing expansion of cross-border M&A had dried up? Our approach to this question consisted in evaluating to what extent greenfield FDI (that is, investment in new assets) would follow an increase in cross-border M&A (the purchase of existing assets). For this purpose, we estimated bivariate vector autoregressions in a pooled cross-country, time-series setting. We worked with annual data for the period 1987-2001 for samples of 22 industrial and 50 developing countries. Table 8 provides a summary of results. We found that an expansion of M&A is indeed followed by an increase in greenfield FDI. According to our estimates, an increase in M&A by 1 percent of GDP leads to a rise in greenfield FDI by about 1 and 1.5 percentage points of GDP in industrial and developing countries, respectively. That is, the subsequent expansion of greenfield FDI is at least as large as the initial increase in M&A, and substantially more in developing economies. Therefore, if the experience of the 1990s and late 1980s is a good predictor for the future, an expansion of greenfield FDI will ensure that the FDI boom will continue in the future even after the privatization process has stopped.

The second question we wanted to address concerns the causality (in the sense of time precedence) between the two forms of FDI and domestic investment and economic growth.

> 18 See Stein and Daude (2001) and Alfaro et al. (2002) for related discussions.

16
|**(name in our**<br>**database)**|||
|---|---|---|
|Corruption<br>(icrg_corrup)|0 to 6|This is an assessment of corruption within the political<br>system. The most common form of corruption met directly<br>by business is financial corruption in the form of demands<br>for special payments and bribes connected with import and<br>export licenses, exchange controls, tax assessments, police<br>protection, or loans. Although our measure takes such<br>corruption into account, it is more concerned with actual or<br>potential corruption in the form of excessive patronage,<br>nepotism, job reservations, 'favor-for-favors', secret party<br>funding, and suspiciously close ties between politics and<br>business.<br>1990-<br>2000<br>**International Country Risk Guide, PRS Group**|
|Law and order<br>(icrg_laworder)|0 to 6|The Law sub-component is an assessment of the strength<br>and impartiality of the legal system, while the Order sub-<br>component is an assessment of popular observance of the<br>law. Thus, a country can enjoy a high rating – 3 – in terms<br>of its judicial system, but a low rating - 1 – if it suffers from<br>a very high crime rate of if the law is routinely ignored<br>without effective sanction.|
|Democratic<br>accountability<br>(icrg_account)|0 to 6|Measure of the government's responsiveness to the people.<br>The score depends on the type of regime: Alternating<br>Democracy, Dominated Democracy, De-facto One-party<br>State, or De-jure One-party State. Higher points are given<br>to Alternating Democracies (see ICRG for details).|
|**Index on Regulato**|**ry Burden**||
||**Components**<br>ENTRY|**Method**|
||TRADE|We apply the following standardization formula to each component described above:|
||FINANCIAL MARKETS|(Xi-Xmin)/ (Xmax-Xmin) if higher values indicate heavier regulation and|
||CONTRACT<br>ENFORCEMENT|(Xmax-Xi)/ (Xmax-Xmin) if lower values indicate heavier regulation.|
||BANKRUPTCY|Therefore, all values are distributed between 0 and 1, with higher values denoting heavier regulation.|
||LABOR REGULATION||
||FISCAL BURDEN|Next we take the simple average of the components in each category to get the corresponding partial indicator. The overall index on<br>regulatory burden is the simple average of the partial indicators.|

44
- (2022). The impact of cash transfers on syrian refugee children in lebanon. _World Development 150_ , 105711.

- Nakamura, E., J. Sigurdsson, and J. Steinsson (2021). The Gift of Moving: Intergenerational Consequences of a Mobility Shock. _The Review of Economic Studies 89_ (3), 1557–1592.

-  ̈Ozler, B., C ̧ . C ̧ elik, S. Cunningham, P. F. Cuevas, and L. Parisotto (2021). Children on the move: Progressive redistribution of humanitarian cash transfers among refugees. _Journal of Development Economics 153_ , 102733.

- Pinotti, P. (2017). Clicking on heaven’s door: The effect of immigrant legalization on crime. _American Economic Review 107_ (1), 138–68.

- Porto, E. D., E. M. Martino, and P. Naticchioni (2021). Back to Black? The Impact of Regularizing Migrant Workers. Working paper, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.

- P ́erez, S. (2021, 02). Southern (American) Hospitality: Italians in Argentina and the United States During the Age of Mass Migration. _The Economic Journal 131_ (638), 2613–2628.

- Romero, N. and L. Uribe (2021). Mecanismos que fortalecen la integraci ́on: Redes de migrantes y permisos de permanencia en los procesos migratorios. _Inter-American Develop-_ .

- _ment Bank Discussion Paper DB-DP-00871_

- Rozo, S. V., A. Quintana, and M. J. Urbina (2023). The Electoral Consequences of Easing the Integration of Forced Migrants. Policy Research Working Paper Series 10342, The World Bank.

- Rozo, S. V. and J. F. Vargas (2021). Brothers or invaders? how crisis-driven migrants shape voting behavior. _Journal of Development Economics 150_ , 102636.

- Tabellini, M. (2019). Gifts of the Immigrants, Woes of the Natives: Lessons from the Age of Mass Migration. _The Review of Economic Studies 87_ (1), 454–486.

36
# **Table 3b: The Impact of Local Elections (PILKADA) on District Government Revenue and Fiscal Balance**

# **per capita: Incumbents vs. Controls and Non-Incumbents vs. Controls**

Treatment: T =1 if district held direct election in 2005; T = 0 if district did not have direct election during 2005-07

|_Variable_|_Coeffi-_<br>_cient_<br>_Revenue from own_<br>_sources_|_Budget surplus_|
|---|---|---|
|**PILKADA**|**Districts where incumbents**|**were re-elected vs.**|
|**Compariso**|**n Districts**||
|T*D06|<br>12,499|202,093***|
||(7,958)|(74,650)|
|# obs|603|605|
|# districts|127|127|

**PILKADA Districts where non-incumbents (new heads) were elected vs. Com** **<u><mark>p</mark></u> arison Districts**

|T*D06<br>|32,696*|1.009e+06***|
|---|---|---|
||(14,610)|(369,377)|
|# obs|569|571|
|# districts|121|121|

Notes:

*: 10% level of significance; **:  5% level of significance; ***: 1% level of significance

Standard errors in parentheses estimated based on fixed-effects model with an AR(1) disturbance (Baltagi and Wu, 1999) Districts that held direct elections during 2006 & 2007 are dropped from the sample used in the regressions.

36
SADC’S INFRASTRUCTURE: A REGIONAL PERSPECTIVE Southern African ports tend to perform somewhat better than those in other African regions across a range of parameters. But, when compared to global best practices, even southern African ports are expensive to use and subject to extensive delays (table 2.6). The services provided by these ports generally cost 75 percent more than other global ports. Crane productivity for containers, while better than some global benchmarks, shows wide variability across ports in southern Africa. Crane productivity for cargo and dwell time for containers is comparable for some ports. The truck-processing time is double that of global ports. Southern African terminals, unlike most other African ports, offer free storage— typically for up to seven days—and thereafter apply a daily storage charge, sometimes on a sliding scale that increases with the number of days.

**Table 2.6 Port performance compared across African regions**

|**Performance**|East Africa|**Southern**<br>**Africa**|West Africa|Global best<br>practice|
|---|---|---|---|---|
|Container dwell time (days)|5–28|**4–8**|11–30|<7|
|Truck-processing time (hours)|4–24|**2–12**|6–24|1|
|Crane productivity (containers per hour)|8–20|**8–22**|7–20|20–30|
|Crane productivity (tonnes per hour)|8–25|**10–25**|7–15|>30|
|**Charges**|||||
|Container handling (US$ per TEU)|135–275|**110–243**|100–320|80–150|
|General-cargo handling charge (US$ per tonne)|6–15|**11–15**|8–15|7–9|

_Source:_ AICD ports database. _Note:_ TEU = twenty-foot equivalent unit.

Individual port performance varies significantly across southern Africa. Some ports are almost as good as the best international ports; others require significant improvement. The ports of Durban and Walvis Bay are among the most efficient in terms of key performance parameters and exceed the performance of all other ports by a large margin (table 2.7). Container dwell time in Beira—a port that could serve northern Zimbabwe and even Malawi—records container dwell times of almost 3 weeks, as does Maputo—which could serve Zambia and Zimbabwe. Crane productivity in Luanda is half that of Durban. Even though prices in Durban are very high and exceed global averages, Durban remains competitive as a transshipment hub. Walvis Bay, which charges half as much as Durban and which is undergoing significant improvements, seeks to claim a growing share of the region’s traffic.

**Table 2.7 Port performance compared across southern Africa**

|**Performance and price**|Cape Town,<br>South Africa|Durban, South<br>Africa|East London,<br>South Africa|Port Elizabeth,<br>South Africa|Walvis Bay,<br>Namibia|Luanda, Angola|Beira,<br>Mozambique|Maputo,<br>Mozambique|
|---|---|---|---|---|---|---|---|---|
|Container dwell time—average (days)|6|4|7|6|8|12|20|22|
|Truck-processing time, cargo receipt and delivery (hours)|5|5|2|5|3|14|7|4|
|Container crane productivity (container per hour)|18|15|8|15||7|10|11|
|Container-cargo-handling charge (US$ per TEU)|258|258|258|258|110|320|125|155|
|General-cargo-handling charge (US$ per tonne)||8|8|8|15|9|7|6|

_Source:_ AICD ports database. _Note:_ TEU = twenty-foot equivalent unit.

29
2. <u>Which alternatives to the service are available? What is the consumption level of the utilities of interest and their close substitutes? Knowing which (energy/water</u> sources, telecommunication or transport) services a household could potentially use (because they are available in the area) as well as which services the household actually uses, helps one to understand to what extent observed patterns of consumption reflect demand decisions or supply constraints. As the reference consumption bundle is defined on the basis of a normative approach, in order to assess how severe the affordability problem is, one must investigate whether spending below the thresholds means that the basic needs are met using cheaper strategies, or not.

3. <u>Which prices and payment schemes are faced by the households? How often do the households fall into arrears with the bills’ payments? Prices affect the</u> household’s decision to switch from one service to the other. Some alternative may not have a market price (e.g. firewood from the forest, water from community standpipes, springs or rivers). For these sources, the survey should provide enough information to evaluate the opportunity cost of such alternatives (for instance by asking for time spent collecting wood or water). Payment schemes may also be crucial for the affordability of the service, with prepayment arrangements often preferred by poor households. Data on arrears are a first indicator of the affordability of the service and they can complement the evidence based on the definition of affordability.

4. <u>Are the services reliable and of good quality? Consumers place value on</u> multiple service attributes, not just costs. The unreliability of the electricity supply motivates a household’s investment in a private power generator, as the poor quality of piped water may drive the consumption of tap water. The poor quality of the service may push consumers towards other solutions (either cheaper or more expensive) in order to meet their needs, with ambiguous effects on the affordability index. Information on quality and reliability can be gathered asking objective questions (for instance about the number of hours each service 22
# **1 Introduction**

Shocks in early childhood can permanently transform an individual’s potential lifetime health, earnings, and cognition. Several variations of this idea, as hypothesis or as stylized fact, are well-known. The lasting effects of nutrition shocks a child experiences in utero and in early childhood are collectively referred to as the “Barker Hypothesis;” specifically before birth, the “fetal origins” hypothesis (Almond and Currie 2011b). Collectively, the windows in a child’s life during which inputs are most important for cognitive development are referred to as “critical” and “sensitive” periods (Knudsen 2004). While early nutritional deprivation can reduce adult height (Hoddinott and Kinsey 2001), early childhood is also a particularly important period for cognition (Cunha and Heckman 2008). Yet because of the demanding longitudinal data required, until recently, very few studies had successfully documented these patterns; fewer still were able to establish causal relationships between external influences early in life and long-term outcomes.

Panel studies have provided one empirical avenue for studying these effects: in Britain, cognitive skills at age seven predict around 20 percent of the variation in adult wages (Almond and Currie 2011a); in the US, parental income shocks in the first several years of a child’s life matters much more for that child’s eventual adult income than do shocks after the child’s fifth birthday (Duncan, Ziol-Guest, and Kalil 2010). In the US, variation in child height early in life predicts test scores later in life, even among children with the same mother (Case and Paxson 2010).<sup>1</sup> A different strand in this literature approaches the problem by showing that specific exogenous environmental shocks have lasting repercussions when they occur in early childhood: in Indonesia, beneficial rains in the year of a girl’s birth increase her adult height by more than half a centimeter, and raise her eventual educational attainment and wealth (Maccini and Yang 2009); in Zimbabwe, drought and civil war during the first two years of a child’s life reduce his eventual height and educational attainment (Hoddinott and Kinsey 2001, Alderman, Hoddinott, and Kinsey 2006). In contrast, the same shocks occurring later in life do not appear to have long-run effects on these outcomes.

> 1Smith (2009) follows a similar approach, showing that in the US, variation in childhood health predicts subsequent household income and wealth, even within families.

1