rafmacalaba/datause-encoder-data huggingface dataset:
# **6 Explaining women’s higher returns to the use of technology**

Understanding FTM’s higher returns to technology adoption is critical for policy. In this section, we describe some tentative channels based on available data. The first possible channel is the link between women’s managerial style and their capacity to optimize technology adoption. For instance, women’s collaborative managerial style (Rosener, 1998) can facilitate employees’ willingness to adopt new technologies and use them productively. Atkin et al. (2017) show that workers can be reluctant to adopt new production methods when incentives are misaligned within firms. Workers can resist adoption in various ways, including by misinforming owners about the value of the technology. Women are more likely to encourage participation by soliciting input from others and keeping open communication channels with their subordinates (Rosener, 1998; Dezs ̈o and Ross, 2012), thus easing workers’ reluctance to use the technologies in the production process productively.

The second potential channel can relate to FTM’s more frequent interactions with universities, suppliers, and buyers, which can strengthen the adoption of certain technologies. For example, in the first wave of the FAT survey in Brazil, Viet Nam, and Senegal, firms were asked about the primary source of external consultants or organizations the establishment used to aid in adopting and using new machines. Figure 4 shows that FTM are substantially more likely to interact with universities when adopting new technologies while less likely to rely on government agencies and business associations. Furthermore, when searching for information about new technologies, Figure 5 shows that FTM are more likely to interact with suppliers and buyers to make decisions. This access to external knowledge can be critical in adjusting the new technologies to the business functions of the firm.

A third potential channel relates to how technology allows women to overcome many social barriers. Women are often responsible for juggling multiple roles, which requires a high level of organizational skills and efficient use of time, which digital technologies can help. For instance, in many countries, women still face restrictions on mobility, meaning that they must operate from home (Bose, 2022). In addition, during the COVID-19 pandemic, evidence suggests that female-managed businesses were particularly harmed by the fact that women needed to balance work with other domestic responsibilities. In this perspective, digitalization has an important role in fostering flexibility in the workplace, thus allowing women to combine entrepreneurial roles with various forms of caring responsibilities, which women generally carry out (Kamaha Njiwa et al., 2023), especially in small businesses.

23
|**Table 3: Evidence of Cognitive and Non-C**|**ognitive Traits**<br>**Total**|**Irrigation**<br>**Kpong**|**Scheme**<br>**Weta**||**Crop Est**<br>**Mode (K**<br>**Broadcast**|**ablishment**<br>**pong only)**<br>**Transplant**||
|---|---|---|---|---|---|---|---|
|**Cognitive skills**||||||||
|Digitspan|5.6|5.7|5.1|***|5.7|5.8|*|
|**Personality traits**||||||||
|Achievement Orientation|1.28|1.29|1.26||1.30|1.27||
|Power Motivation|0.80|0.84|0.71|**|0.88|0.80||
|Tenacity|1.34|1.37|1.26|***|1.37|1.38||
|Work Centrality/Passion Composite|1.49|1.47|1.53|*|1.49|1.45||
|Internal Locus|-0.15|-0.17|-0.10|*|-0.21|-0.13|*|
|Optimism|0.62|0.51|0.88|***|0.47|0.56|**|
|Polychronicity|-0.72|-0.78|-0.58|***|-0.81|-0.76||
|Organization|1.39|1.41|1.32|**|1.43|1.40||
|Impulsiveness|-0.37|-0.40|-0.30|***|-0.40|-0.40||
|Number of Observations|1194|845|349||421|424||

_Source:_ Own computation from World Bank Kpong and Weta irrigation scheme survey. Asterisks denote significance of t-tests for equality of means between the preceding columns: *** p<0.01, ** p<0.05, * p<0.1.

19
# **1 Introduction**<sup>1</sup>

Developments in the U.S. economy, because of its size and international linkages, are bound to have substantial implications for the global economy. The United States is the world’s single largest economy (at market exchange rates), accounting for almost 22 percent of global output and over a third of stock market capitalization. It is prominent in virtually every global market, accounting for about one-tenth of global trade flows, one-fifth of global FDI stock, close to one-fifth of remittances, and one-fifth of global energy demand. Since the U.S. dollar is the most widely used currency in global trade and financial transactions, changes in U.S. monetary policy and investor sentiment play a major role in driving global financing conditions.

At the same time, the global economy is important for the United States. Affiliates of U.S. multinationals operating abroad and affiliates of foreign companies located in the United States account for a sizable share of output, employment, cross-border trade and financial flows. One-sixth of consumer goods purchases by U.S. consumers are for imported goods, with an even higher share in cars and consumer electronics.

While there is an extensive body of work that examines different aspects of the role of the U.S. economy and the global spillovers it generates, the literature lacks an integrated and comprehensive overview on this important topic.<sup>2</sup> The paper fills this gap in the literature by providing an overview of the role of the United States in the global economy and quantifying the global spillovers from changes in U.S. growth, monetary and fiscal policies, and uncertainty in its financial markets and economic policies. Specifically, the paper addresses four major questions. First, how important are economic linkages between the U.S. economy and the world? Second, how synchronous are business cycles in the United States and other economies? Third, how large are global spillovers from shocks originating in the United States? Finally, how important is the global economy for the United States?

The rest of the paper is organized as follows: Section 2 examines the economic linkages between the United States and the world economy focusing on trade, financial and commodity markets; Section 3 explores the synchronization of U.S. and global business and financial cycles; Section 4 quantifies the extent to which changes in U.S. growth spill over to the global

> 1This paper draws from a background study featured in World Bank 2017. Figures and background data presented here are available at www.worldbank.org/gep.

2 Some studies focus on the magnitude of real and financial spillovers from the United States and other advanced economies (World Bank 2016a; IMF 2015a and IMF 2015b; Arteta et al. 2015). Shambaugh (2016) examines the importance of global growth for the U.S. economy.

1
Table 2.4

||**I**|**ntegrationwi**|**ththeGlobalEcono**|**my**|||
|---|---|---|---|---|---|---|
||<br>**TradeInG **|<br>**oods'**|**GrossPrivateCa**|**pitalFlows**<sup>**2**</sup>|**Gross**|**FDI3**|
||**%ofG**|**DP**|**%ofGD**|**P**|**%ofG**|**DP**|
||**1990**|**2000**|**1990**|**2000**|**1990**|**2000**|
|Cambodia|**22.4**|**40.2**|**3.2**|**6.8**|**1.7**|**3.9**|
|Indonesia|**41.5**|**62.4**|**4.1**|**8.5**|**1.0**|**4.2**|
|LaoPDR|**32.3**|**52.7**|**3.7**|**8.7**|0.7|**5.4**|
|**Malaysia**|**133.3**|201.3|10.3|16.8|5.3|**2.0**|
|Philippines|47.6|**98.5**|**4.4**|48.4|1.2|**2.8**|
|Singapore|309.9|295.3|54.6|48.5|20.7|11.6|
|Thailand|66.1|107.2|13.|**11.3**|3.0|**2.8**|
|Vietnam|79.7|96.0|n.a|10.8|n.a.|4.1|
|China|32.5|43.9|2.5|12.7|1.2|**4.3**|
|Hong Kong,China|223.5|256.2|n.a.|188.8|n.a.|89.2|
|Japan|17.1|17.7|5.4|10.3|1.7|**0.9**|
|Korea|53.4|72.8|6.2|11.5|0.7|**3.2**|
|Canada|43.8|75.8|8.1|30.0|2.7|16.1|
|Mexico|**32.1**|**60.8**|**9.2**|**6.3**|**1.0**|**2.3**|
|UnitedStates|15.8|20.7|**5.7,**|16.9|**2.8**|5.1|
|EastAsia&Pacific|48.8|**65.6**|**5.3**|**13.3**|1.5|**3.9**|
|Europe EMU|44.9|**56.3**|14.1|**49.31**|2.9|14.8|

1. The sum of merchandise exports and imports measured in current U.S. dollars, **divided** by the value of GDP in U.S. dollars.

2. The sum **of** the absolute values cf direct, portfolio, and other investment inflows and outflows recorded in the balance of payments financial accoLnt, excluding changes in the assets and liabilities of monetary authorities and general govemment.

3. The sum of absolute values **of** inilows and outflows of FDI recorded in the balance of payments financial account. This indicator differs from the standard measure **of** FDI, which captures only inward investment Note: Data not available for Brunei Darussalam, Myanmar, and Taiwan; data for some countries may be for a year different than indicated.

Source: The World Bank, **Worid** Demelopment Indicators 2002, Table 6.1, pp 332-334.

The East Asia and Pacific region has a considerably higher trade/GDP ratio (66 percent in 2000) than that of the European Monetary Union (EMU) and NAFTA (i.e., Mexico, the U.S. and Canada shown separately in the above table). There is a significant difference in the level of this ratio almong the individual East Asian economies with Singapore and Hong Kong at the higher end, reflecting their roles as entrepots, and China and the smaller ASEAN countries at the lower end, reflecting the slower opening of their economies.

Another important indicator of the degree of openness in trade is the import tariff, 1<sup>4 8</sup> which has been r educed significantly over the last decade largely due to the effects of regional and global trade arrangements. (See Figure 2.5 below.) 41
||**App**<br>|**endix Table**<br> <br>_1 if At_|**3: First Stag**<br> <br>_tended Daycare_|**e**<br> <br>_for..._||
|---|---|---|---|---|---|
||0 Years|1 Year|2 Years|3 Years|4 Years|
|Treatment|-0.19|-0.02|0.05|0.10|0.07|
||[0.02]|[0.02]|[0.02]|[0.02]|[0.02]|
|Mean of Y||||||
|_Notes_: The table sh<br>among Control|ows that treatme<br>0.22|nt children wer<br>0.17|more likely to<br>0.22|attend daycare t<br>0.26|han the control<br>0.13|

_Notes_ : The table shows that treatment children were more likely to attend daycare than the control. The dependent variables are indicators for participants attending daycare for 0, 1, 2, 3, and 4 years. _N_ = 1,857 .

38
Afonso, Furceri and Gomes (2012) use an event study analysis to demonstrate significant responses of EU government bond yield spreads to changes in ratings and outlooks, particularly in the case of negative announcements.

Kaminsky and Schmukler (1999) find that during the Asian financial crisis, news about agreements with international organizations and credit rating agencies had the most impact on stock prices. Kaminsky and Schmukler (2002) find that sovereign rating and outlook changes in emerging markets impact not only bond spreads but also stock prices. Impacts of changes are stronger during crises and also generate cross-country contagion. Ferreira and Gama (2007) find that sovereign rating and credit outlook changes of one country have an asymmetric and economically significant effect on stock market returns of other countries. A credit rating downgrade has a negative reaction around the world, but upgrades have no significant impact abroad. Alsakka and ApGwilym (2012) find that rating agencies’ signals affect a country’s exchange rate and also have strong spillover effects on exchange rates of other countries in the same region.

A study by Guscina, Pedras, and Presciuttini (2014) finds that improvements in sovereign ratings have often preceded bond issuances by first-time issuers. The quality of institutions, GDP growth, reduction in debt, and improvement in global risk conditions are all associated with lower cost of borrowing by new issuers. These issuers face a premium over established emerging markets; this additional cost of borrowing tends to rise together with worsening global risk.

A new strand of literature has explicitly formulated the concept of relative risk ratings. Basu et al. (2012) define a new relative performance index and then track how nations have done over time. According to them, major credit rating agencies assign sovereign credit ratings as an absolute grade. In contrast, relative risk ratings indicate how a particular sovereign fares in relation to the rating performance of other sovereigns. Basu et al. (2013) compare relative ratings in 2012 with those of early 2008 and find that while they improved in several developing economies, they deteriorated in crisis-affected high-income countries. Interestingly, India, Jordan, Poland, and the United Kingdom had outlook downgrades, but their relative ratings improved as other countries suffered even worse downgrades. The implications of this have not yet been examined in the literature and this is a gap we seek to address.

6
32 Machin, Stephen, and Costas Meghir. 2000. Crime and Economic Incentives. _The Institutefor Fiscal Studies Working Paper,_ 00/17.

Merton, Robert K. 1938. Social Structure and Anomie. _American Sociological Review,_ Volume 3, Issue 5, pp. 672-682.

Mistiaen, Johan, Berk Ozler, Tiaray Razafimanantena, and Jean Razafindravonona. 2002. Putting Welfare on the Map in Madagascar. Africa Region Technical Working Paper Series No. 34. The World Bank.

Pradhan, Menno, and Martin Ravallion. 1999. Who Wants Safer Streets? Explaining Concern for Public Safety in Brazil. Processed.

Rama, Martin. 2001. Labor Market Issues in South Africa. Processed. The World Bank.

Victims of Crime Survey. 1998. Statistics South Africa.

Wilson, Margo, and Martin Daly, 1997. Life Expectancy, Economic Inequality, Homicide, and Reproductive Timing in Chicago Neighborhoods. _British Medical Journal,_ 314:1271.
**Hanousek, Jan, Evžen Kočenda, and Jan Svejnar.** 2007. “Origin and Concentration: Corporate Ownership, Control, and Performance in Firms after Privatization.” _Economics of Transition_ , 15(1): 1-31.

**Hanousek, Jan, Evžen Kočenda, and Jan Svejnar.** 2008. “Divestitures, Privatization and Corporate Performance in Emerging Markets. Forthcoming in _Economics of Transition_ .

**Hansen, Nico A.** 1997. “Privatization, Technology Choice and Aggregate Outcomes.” _Journal of Public Economics_ , 64(3): 425-42.

**Hart, Oliver D. and John Moore** . 1988. “Incomplete Contracts and Renegotiation.” _Econometrica_ , 56(4): 755-85.

**Hinds, Manuel.** 1990. “Issues in the Introduction of Market Forces in Eastern European Socialist Economics.” In _Managing Inflation in socialist Economies in Transition_ , ed. Simon Commander. Washington, D.C.: World Bank.

**Hu, Yifan, Frank Song, and Junxi Zhang** . 2004. “Competition, Ownership, Corporate Governance and Enterprise Performance: Evidence from China.” Hong Kong Institute of Economics and Business Strategy Working Paper 1111.

**Jefferson, Gary H. and Jian Su.** 2006. “Privatization and restructuring in China: Evidence from shareholding ownership, 1995–2001.” _Journal of Comparative Economics,_ 34(1): 146–166.

**Jia, Jin, Qian Sun and Wilson Tong. 2005. “Privatization via an Overseas Listing: Evidence from China's H-Share Firms.”** **_Financial Management_ , 34(3): 5-30.**

**Johnson, Simon, Rafael LaPorta, Florencio Lopez-de-Silanes, and Andrei Shleifer** . 2000. “Tunneling.” _Law and Economic Development_ , 352-57.

**Jones, Derek C.** 2004. “Ownership and participation: A review of the empirical evidence for Transition Economies”. _Advances in the Economic Analysis of Participatory and Labor managed Firms_ , 8: 171-209,

**Jones, Derek, Mark Klinedinst, and Charles Rock.** 1998. “Productive Efficiency during Transition: Evidence from Bulgarian Panel Data.” _Journal of Comparative Economics_ , 26(3): 446-64.

**Jones, Derek C., and Niels Mygind.** 2002. “Ownership and Productive Efficiency: Evidence from Estonia.” _Review of Development Economics_ , 6(2): 284-301.

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36
places, the right to use the land is allocated by the community; the rights may provide longterm tenure security or may be quite vulnerable to transfer. To develop measures that are both internationally comparable and locally relevant, one approach is to define ownership as the strongest bundle of rights possible in that context.

To measure control and use rights, surveys have used two approaches. One is to ask about the rights that individuals have over property. These may include the right to transfer (through sales or bequests) or the right to manage or change the asset (such as by planting permanent crops or building terraces). The second is to ask about who makes decisions about the property, such as what to plant on the land.

While numerous studies focus on a particular set of rights, claiming that the other rights are correlated, no systematic study has considered the correlation across the bundle of rights in a variety of contexts. The one paper that does this only considers six countries in Africa. It finds that ownership, management, and control over output do not necessarily overlap and that the patterns differ markedly across contexts and for men and women (Slavchevska et al, 2017). It would be useful to compare these rights across a broader range of contexts.

# **4.2 Exclusive and Joint Ownership**

Any of the property rights discussed above—ownership, control, and use—may all be held individually or jointly.<sup>18</sup> Much of the literature on asset ownership as an indicator of women’s bargaining power has not considered whether the property is owned individually or jointly. Depending on the marital regime, assets acquired within marriage may be owned jointly or individually. Further, the social norms regarding ownership within marriage may or may not match the legal regulations. Ownership may also be shared intergenerationally; the transfer of land and housing may happen over time as the parents turn over responsibility for the farm to their children.

There are two approaches to identifying individual and joint ownership, again based on the unit of analysis at the level of the assets or of the individuals. First, if the data are collected about each asset, it is possible to identify the owner(s) of each asset. Then, for each asset we know whether it is owned individually or jointly and by whom. The second approach asks each individual respondent who owns any of a specific asset type, whether they own it individually, jointly, or at least one individually and one jointly.

> 18 In addition, some property such as land may be held by a community as common property. There are a range of issues regarding how to obtain data on common property which are beyond the scope of this study.

18
ANGOLA’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE

# Power

## **Achievements**

Angola has been making substantial investments in the power sector since 2002 to restore and reconstruct the infrastructure that was destroyed during the civil war. Recent estimates from Empresa Nacional de Electricidade (ENE)—Angola’s major power-generating company—indicate that these investments led to an increase in generation capacity from around 830 MW in 2002 to over 1,200 MW in 2008 (World Bank 2010a) (table 2). In terms of per capita generating capacity, Angola fares better than the average African fragile state or resource-rich country. Angola has 70 MW per million people compared to resource-rich or low-income fragile countries, which have only 43 or 46 MW per million people, respectively (table 1).

Furthermore, a relatively high share of Angola’s generation capacity is actually operational. In 2008 almost 1,000 MW or 80 percent of the installed power generation capacity was operational. This is higher, on average, than resource-rich countries, where roughly 66 percent was operational and generating power. Thus, Angola has been able to rapidly ramp up its power production over the past decade. This increased generation and operational capacity facilitated a 13 percent average annual growth in power production between 1999 and 2008. As of 2008 around 4,133 GWh of power was produced, a steep increase compared to 1999 production levels of 1,295 GWh (World Bank 2010a).

The delay involved in obtaining an electricity connection has fallen dramatically since 2007. Investment climate surveys in 2007 reported that firms encountered delays of over two months in Luanda and over six months in other parts of Angola in order to obtain a new electricity connection (World Bank 2007b). But Angola has achieved tremendous progress in this area—firms in 2010 recorded only a sevenday delay, on average, in obtaining a power connection (World Bank 2010b).

## **Challenges**

But increased investments in power infrastructure have not necessarily translated into widespread electrification. As of 2008 only a little more than 30 percent of Angola’s population benefited from access to power, lower than the 46 percent average for the nation’s resource-rich African peers. No disaggregated data are available on the levels of rural versus urban access in Angola (World Bank 2010a), but it is known that Luanda consumes around two-thirds of the nation’s electricity, suggesting relatively high access in the urban and peri-urban areas of the capital. Further, at least 85 percent of Luanda’s municipalities indicate that they use electricity for lighting, corroborating that the availability of electricity in urban areas is high (World Bank 2005). It is estimated that about half of the connected residential consumers in Luanda are served by informal providers who pay a bulk tariff of around US$0.04 cents per kilowatt-hour to the utility and resell to consumers at approximately three times this price. Given the limited attention given to rural electrification to date, rural access can be expected to be quite low.

10
the new mechanism, explain it, and then take steps to devalue to the desired level in a more measured fashion. This would allow corporates and investors to plan for the adjustments and reduce the shock premium that the move will command. The danger is that where the market is shocked it will overreact...” (Stockbrokers Botswana 2005: 1).

This qualitative evidence supports two important points: First, neither the devaluation nor its timing was anticipated by the general public, and not even by businesses operating in currency markets. In that sense, it was an “exogenous” economic shock to citizens and the outcome we study, subjective evaluations of well-being. Second, although citizens are able to self-select into categories (like living in an urban area) that are correlated with treatment assignment, neither respondents nor the _Afrobarometer_ had information, incentive, or capacity to decide whether respondents were interviewed before or after the devaluation, making direct self-selection into treatment highly improbable. Rather, the currency devaluation by the Bank of Botswana was an event that demarcated the respondents of the _Afrobarometer_ survey into two groups, not because of the knowledge or decisions of respondents, but simply by chance. In Appendix S1, we provide further tests of the equivalence of the treatment and control groups on socio-economic background variables. Appendix S2 and S3 also shows results from regression and matching for observations that are on common support on the propensity score. These results do not change the main conclusions below.

# **III. Devaluation and Well-Being: Simple Pre- and Post-Treatment Comparisons**

To get a sense of the differences between pre- and post-treatment groups, this section shows the simple relationship between exposure to the devaluation and subjective well-being, as well as the development in food prices in the months surrounding the devaluation. The latter is important 12