rafmacalaba/data-use-mentions-extended huggingface dataset:
in values:<sup>21</sup> _Aj/γj_ , the preference-adjusted technology, is calibrated using Equations (11) and (12). As the value of domestic income and expenditure calculated from the trade data do not perfectly match up, we dene _ψj ≡ Ej/_ � _Yj_ + _ηj_ � _i∈_ N _ji,t_<sup>_φiYi−φjYj_</sup> � _i∈_ N _ij,t_<sup>_ηi_</sup> � as an exogenous country-specic parameter that accounts for these trade imbalances. In the spirit of Dekle et al. (2007, 2008), we rst eliminate all exogenous trade imbalances and take the equilibrium without trade imbalances as baseline.

In order to highlight the alternative channels through which DTAs aect FDI, and also to capitalize on the full set of our partial estimates, we perform two sets of experiments. First, we rely on our estimates of the dummy variables for DTAs and DTAs with investment provisions from column (2) of Table 1 and column (3) of Table 2, respectively. Then, we also obtain corresponding eects based on the estimates of the continuous depth variables from column (3) of Table 1 and column (4) of Table 2. Consistent with the discussion in Section 2.2, we perform each of the two experiments in two steps. First, we change the vector of FDI frictions. Then, in addition, we change the vector of trade costs. As the DTAs are already in place, we perform an ex-post evaluation, i.e., we assume that in the baseline the agreement is in place and simulate the eect without DTAs as counterfactual. We then report the change from the baseline to the counterfactual, i.e., baseline value minus counterfactual value relative to the counterfactual value.

> 21 The values of _ωij_ are restricted to be between zero and one. Hence, we normalize each row by the
those who pursued attainment of the extrinsic aspirations for money, fame, and image.

Another psychological argument, known as the ―Yerkes-Dodson law‖, highlights the phenomenon of ―choking under pressure‖ (Ariely, Gneezy, et al. 2009). If individual salary is subject to high-stakes pressure, individuals experience increased arousal and shift from automatic to controlled behavior, a narrowing of attention and a pre-occupation with the reward, all lessening the chances of success. The argument is that performance has an ―inverse U‖ relationship with the level of the incentive payment, with performance improving at low and moderate levels of incentive payments as compared to no payments, but then being worse at very high levels of payment compared to moderate, low, or even no payments.

Lastly, behavioral economists have identified the possibility of satisficing instead of maximizing behavior. Employees might exert effort until a certain minimum level of reward is reached and then substitute additional labor supply for increased leisure or idle time. A study of New York cab drivers identified the prevalence of satisficing behavior and questions the effectiveness of performance pay schemes, if the satisficing threshold is hit quickly (Camerer, Babcock, et al. 1997).

The proponents of ―self-determination theory‖ clearly have a strong and intuitively attractive point to make, but it is not evident that the case for intrinsic incentives overwhelms consideration of extrinsic incentives. Three areas of uncertainty hang over conclusions in this area. First, autonomy, mastery and purpose are more feasible in some tasks than in others. Second, intrinsic motivation can take two forms — being motivated by the inherent nature of the job or being motivated to earn the respect of one‘s peers — and group-based performance schemes, to the extent that they encourage teamwork, could increase intrinsic motivation. Finally, the theory is largely addressing the moral hazard problem inherent in principal-agent relationships, suggesting that staff can sense that they are being treated instrumentally through the use of extrinsic incentives and so will be motivated to cheat. There are different implications for
**Table A1.3: Bias in beta estimation due to investment horizon length**

|**Type**|**Assumed investment**|**Assumed investment**|
|---|---|---|
||**horizon is too long**|**horizon is too short**|
|Aggressive stock (J > 1)|Beta is over-estimated|Beta is under-estimated|
|Neutral stock (J3=1)|Beta is correctly estimated|Beta is correctly estimated|
|Defensive stock**(**<1)|Beta is under-estimated|Beta is over-estimated|

The authors argue that the true horizon for most investors is likely to be more than a year, thus estimates based on a period length shorter than this will tend to underestimate high beta values and over-estimate low ones.

# **A1.3.4 International differences in interval effects**

The biases in estimated beta values for different national markets are unlikely to be of the same degree and may not even be in the same direction. First, the availability of quotation data for some markets should reduce misestimation in these cases, while serious biases remain in other markets. Second, differences in transaction costs and trading methods may affect the extent of adjustment delays and non-synchronous trading problems, such that the degree of autocorrelation in market returns, varies between countries.

Third, there is some evidence that the size of the relevant stock market affects the seriousness of the intervalling effect. Berglund et al. (1983)13 find the length of the adjustment process to be related to the total turnover of the exchange rather than the trading frequency of the particular stock, such that adjustment takes longer in a small stock market. Martikainen and Perttunen (1991)14 demonstrate that, contrary to the findings of Handa _et al._ (1989), the size effect tends to increase rather than decrease with the return interval in a thin stock market.

>
|
|Tafiela|-0.2|1.1|
|Ma'an|-0.4|2.3|
|Aqaba<br>Source: World Bank Staff Calculat<br>Expenditure Surveys.|-0.3<br>ions using Official Hou|1.7<br>sehold Income and|

On another note, the three-fold decomposition of the Gini coefficient over the period 2002-2010 reveals that the inequality in Jordan is also driven by consumption level differences among the various regions in the Kingdom. Table 6 indicates that the within-group inequality is the major component of overall inequality that has been increasing over time. Indeed looking at the urban-rural grouping, the share of the within-group component has increased from 68.2 percent of total inequality in 2002 to 74.4 percent in 2010 and hence dominates the betweengroup component. This suggests that the reduction in inequality, observed in the past decade in Jordan, has been mainly driven by more equitable income distribution within residents of each area, rural and urban, rather than by differences in average real income.

However, when considering the governorate groupings, calculations yield different findings. In this case, Table 6 indicates a slightly more dominant role for between-group effect (33 and 27.8 percent in 2002 and 2010 respectively) along with a significant contribution of the 20
Kuziemko, I., M. I. Norton, E. Saez, and S. Stantcheva. 2015. “How Elastic Are Preferences for Redistribution: Evidence from Randomized Survey Experiments.” American Economic Review 105 (4): 1478–1508.

Ladronis, Julieta, Juan Cruz Lopez de la Valle and Valentina Martinez. 2019. “CEQ Master Workbook: Argentina (2017),” CEQ Data Center on Fiscal Redistribution (CEQ Institute, Tulane University). Aug 18, 2019.

Lara Ibarra, Gabriel, Nistha Sinha, Rana Nayer Safwat Fayez, Jon Jellema. 2019. "Impact of Fiscal Policy on Inequality and Poverty in the Arab Republic of Egypt". Policy Research working paper; no. WPS 8824 (Washington: World Bank).

Mahdavi, P., C. Martinez-Alvarez, and M. Ross. 2022. “Why Do Governments Tax or Subsidize Fossil Fuels?” Journal of Politics 84 (4): 2123–39.

Martinez-Alvarez, C., C. Hazlett, P. Mahdavi, and M. Ross. 2022. “Political Leadership Has Limited Impact on Fossil Fuel Taxes and Subsidies.” PNAS 119 (47): e2208024119.

McCulloch, N. 2023. Ending Fossil Fuel Subsidies: The Politics of Saving the Planet. Oxford, UK: Practical Action Publishing.

McCulloch, N., T. Moerenhout, and J. Yang. 2021. “Fuel Subsidy Reform and the Social Contract in Nigeria: A Micro-economic Analysis.” Energy Policy 156.

McCulloch, N., D. Natalini, N. Hossain, and P. Justino, P. 2022. “An Exploration of the Association between Fuel Subsidies and Fuel Riots.” World Development 157 (September).

53
main variables used in the analysis.<sup>19</sup> Figure 3 shows the top 10 origin countries for refugees arriving in Switzerland between 1998 and 2018. Most refugees in this period came from Eritrea, the second biggest group came from Syria, followed by Afghanistan. The biggest wave of refugees came to Switzerland in the year 2015.

In the second part of the empirical analysis, where we examine the role of the initial conditions, we focus on the universe of refugees and we add information on three different conditions in the canton of arrival at the time of arrival. The first condition we analyze is the unemployment rate. This data is measured yearly at the cantonal level and comes from the State Secretariat of Economic Affairs (SECO). The second dimension, we are looking at is the network of migrants and refugees from the same origin country residing in the arrival canton at the time of arrival. The variable co-ethnic network is defined as the log number of co-nationals, measured at the canton level. The third aspect we are focusing on are attitudes towards migrants and natives in the canton of arrival, measured by voting outcomes. The voting data comes from the FSO and the construction of our indicator is described in the remainder of this section.

# **Attitudes toward migration and asylum**

To measure attitudes toward migration and asylum, we construct a time-varying indicator at the canton level, which is based on cantonal vote outcomes. The Swiss (semi-)direct democracy provides an ideal context to measure attitudes over time at a detailed geographical level. Between 1996 and 2020, Swiss voters were asked to vote 21 times on issues related to migration and asylum. A complete list of these votes is provided in Table A.1 in the appendix. There are three types of votes: popular initiative (a proposal to change the constitution, which can be initiated by a group of citizens with 100’000 signatures), mandatory referendum (the parliament proposes to change a constitutional article or an international
related to poverty mapping.) For examples of surveyto-survey imputation for poverty analysis, see Stifel and Christiaensen (2007), Tarozzi (2007), Grosse et al (2009), and Douidich et al (2013).

A more formal presentation of the S2S model is as follows. There are surveys: in Survey 1 there are information on the income or consumption as well as the set of household characteristics ���. In the Survey 2, the same set of household characteristics are also observed, and those characteristics are comparable between the two surveys.

The (log) of per capita household income or consumption is modeled for the first survey as: ��� ��′������� where ��� is the per capita income or consumption of household _h_ residing in area _c_ , ��� are household and area/location characteristics, and ��� ��� ���� is the residual composed of the area component �� and the household component ���, which have zero expectations and are independent of each other.

In the second survey where there is no income or consumption information, a set of common variables ��� will be use to impute the income or consumption for each household in the second survey using the estimated points and their distributions estimated from the survey 1. Since each estimated point is fluctuated from an assumed normal distribution with its standard errors, the imputation is done through a number of simulation in order to preserve the error structure of the correlates.

58
the measure proposed in a country like Morocco and, more generally, in North-Africa and the MiddleEast where the gender divide in the labor market is very important and still little understood.

# **4. Data**

This paper uses data from the Morocco Household and Youth Survey (MHYS) of 2009–2010. This survey was undertaken by the World Bank to study economic and civic exclusion of the young population in Morocco. The survey collects information on all household members with a stronger focus on the youth (aged 15-29) within the households.<sup>4</sup> The MHYS 2009-2010 is a nationally representative survey of 2,000 households, of which 1,216 households are urban and 784 are rural. The survey collected information on household members’ demographic and educational characteristics, as well as their economic activities. Information was also collected on household assets and expenditure, the ability of households to cope with shocks, their use of social assistance, and migration behavior. In addition, the MHYS administered a separate instrument with additional questions on aspects of employment and civic participation to 2,883 young individuals aged 15 to 29 (representing about 90 percent of the youth in the surveyed households).

The paper first looks at income inequality and relative deprivation using the entire sample of 2,000 households that covers 10,769 individuals. The expenditure module of the MHYS was used to construct a household level expenditure aggregate, which was adjusted for cost of living differences across rural and urban areas.<sup>5</sup> As it is standard in the measurement of welfare in middle income and poor countries, expenditure is preferred to income as income is often underreported and more volatile than expenditures. Hence, the expenditure aggregate is used as the household level indicator of wellbeing.

We then shift to the analysis of relative labor deprivation where the sample is limited to those individuals aged between 15 and 64 who are not enrolled in school. This restricts the sample to 6,451 individuals – 3
.527)|(0.904)|(0.629)|(0.746)|(0.398)|
|Round FEs|YES|YES|YES|YES|YES|YES|YES|YES|YES|
|Fixed Effects (FEs)|HH|HH|HH|HH|HH|HH|HH|HH|HH|
|Controls|YES|YES|YES|YES|YES|YES|YES|YES|YES|
|R-squared|0.019|0.021|0.058|0.043|0.054|0.070|0.026|0.036|0.064|
|# of EAs|433|290|143|433|290|143|433|290|143|
|N|13520|9734|3786|13518|9732|3786|13520|9734|3786|

_Notes:_ This table provides estimates of the impacts of logarithm of refugee intensity on whether a household is negatively affected by a fall in prices of food items (the first three columns), a rise in prices of food items (the middle three columns), and a rise in prices of agricultural inputs (seed and fertilizer) (last three columns). Household sample weights from ESS2 applied. Columns labeled “All,” “Rural,” and “Urban” report results for all, rural, and urban households, respectively. All columns control for household (HH) FEs, round FEs, and 12 time-varying characteristics. The coefficient estimates for these 12 control variables are not reported here, but can be available on request. Robust standard errors clustered at EA level are given in parenthesis. Asterisks: *, **, and *** indicate statistical significance at 10%, 5%, and 1% levels, respectively.

50
measured in dollars of 1995. gdp growth, growth, is de...ned as real per capita gdp growth rate. The real interest rate, r, is the lending rate adjusted for the rate of growth of the gdp de‡ator. In‡ation, inf, is measured as the growth rate in the consumer price index. Annual time series of each of the variables were obtained from The World Development Indicators.

Financial deepening, fd, is de...ned as time and saving deposits, tsd, divided by gross national disposable income, gndi. Edwards (1996) uses M2/GDP for this variable. In our case we cannot use that variable because M2 is no longer a meaningful concept in euro countries.<sup>24</sup> The foreign saving ratio, fsr, is de...ned as foreign saving (i.e., minus the current account, ca) divided by gross national disposable income, gndi. Annual time series of each of the variables were obtained from The World Development Indicators.

The social expenditure ratio, ser, is de...ned as social expenditure, se, divided by gross national disposable income, gndi. Annual time series of social expenditure were obtained from The Government Financial Statistics.

We will start our empirical analysis of the e¤ects of pension saving on national saving by running a simple regression model exploiting both cross country and time variability. The total number of observations is 472. The estimated equation is (t statistics in parenthesis): These results suggest show that there is a negative correlation between national saving and pension saving but it is not statistically signi...cant.

> 24The reason is that currency, a component of M2, cannot longer be associated to a particular country.

29
gration movements. For example, McKenzie (2008) shows that the peak age of migration for developing country migrants is 24 in many destination countries, and that the majority of these young migrants are not married at the time of migrating. Our analysis of the ACS documents that the majority of adult working age immigrants in the U.S. do change their marital status after migration. A large literature documents how the prospect of migrating in the future determines investments in human capital, showing that many individuals are thinking ahead to the possibility that they might migrate. So, even the possibility of migration may help shape family formation and stability. The result is that most studies that aim to look at the impacts of family on migration decisions, and of the impacts of migration on spousal and child well-being, will need to carefully consider the issues raised here.

# **6 Conclusions**

Migration changes whether and how families form and dissolve, how individuals value proximity to others, and whose utility ends up factoring into an individual’s decision-making process. While the literature has long recognized the importance of the family in determining migration decisions, it has paid much less attention to the role of the counterfactual family. Recognizing that different migration choices will result in different families can mean that migration decisions are dynamically and locally inconsistent. The inability to visualize what one is giving up in terms of potential family when choosing not to migrate may create a bias towards non-migration. In addition to changing how we model and theorize about migration decisions, this also has implications for efforts to measure impacts of migration on family members, and for data collection, as standard surveys provide little to no information about the migrants’ family, or about when it has formed or changed.<sup>26</sup> Taking into account the counterfactual families associated with migration suggests several directions and implications for policy efforts. First, many of the details of migration policies will have impacts on decisions of families to form and stay together or dissolve, and
in the Caribbean from LLI (2021).<sup>13</sup> The data offer comprehensive information on ports of call by freight hauling vessels in the Caribbean during the years 2004-2020. Each observation reports the previous five and subsequent five ports of call by the ship in question, as well as a unique vessel ID number. We also purchased from LLI data on characteristics of the 16,097 freight-hauling vessels in our database. The following information is available for nearly every vessel: the vessel identification number, vessel type, flag of registry, year and place of build, the vessel’s owner, and its dead-weight tonnage (DWT). We combine the port of call data with the ship characteristics data to describe the supply of vessels that call in Caribbean or PR ports, as well as those that meet JA criteria, The LLI data understate the volume of barge traffic between the U.S. and PR. We also use data from the National Ballast Information Clearinghouse (NBIC, 2024), which reports data that is similar to that of LLI, but only for U.S. ports. The NBIC data are publicly available, another advantage. We report port-of-call data from both series for 2019 because it is the most recent year of LLI data not affected by the COVID-19 pandemic.

# **3.2 Puerto Rican import data**

Our empirical gravity model relies on data documenting flows of imports into PR. These data are provided by IEPR (2021) for 2010-2017. The data report monthly imports to PR disaggregated by HS10-digit product code, origin country (for foreign imports) and U.S. customs district (for U.S.-origin shipments).<sup>14</sup> The data report the value of imports (defined in FOB terms) and imported quantities (in kg.).<sup>15</sup> 13Taylor (2021) uses these data to study the impact of large vessels on the reproduction rates of
Policy Research Working Paper 10593

# **Abstract**

This paper examines the reshaping of supply chains using detailed US 10-digit import data (tariff-line level) between 2017 and 2022. The results show that while US-China decoupling in bilateral trade is real, supply chains remain intertwined with China. Over the period, China’s share of US imports fell from 22 to 16 percent. The paper shows that the decline is due to US tariffs. US imports from China are being replaced with imports from large developing countries with revealed comparative advantage in a product. Countries replacing China tend to be deeply integrated into China’s supply chains and are experiencing faster import growth from China, especially in strategic industries. Put differently, to displace China on the export side, countries must embrace China’s supply chains. Within products, the reorientation of trade is consistent with a “China + 1” strategy, as opposed to diversified sourcing across multiple countries. There is some evidence of nearshoring, but it is exclusive to border nations, and there is no consistent evidence of reshoring. Despite the significant reshaping, China remained the top supplier of imported goods to the US in 2022.

This paper is a product of the Office of the Chief Economist, East Asia and the Pacific Region and the Prospects Group, Development Economics. 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 clfreund@ucsd.edu, amattoo@worldbank.org, amulabdic@worldbank.org, and mruta@imf.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
.uk/~timm/grid/CRU_TS_2_1.html.

Mueller, Valerie, and Daniel, Osgood, 2009, Long‐Term Impacts of Droughts on Labour Markets in Developing Countries: Evidence from Brazil, _Journal of Development Studies_ , 45‐10: 1651‐1662.

- Mueller, Valerie and Agnes, Quisumbing, 2010, Short‐ and long‐term effects of the 1998 Bangladesh flood on rural wages, _IFPRI discussion papers 956_ , International Food Policy Research Institute.

- NIMA (National Imagery and Mapping Agency).  1997. _World Roads_ .  Fairfax, VA: National Imagery and Mapping Agency.  Available at:

https://www1.columbia.edu/sec/acis/eds/dgate/studies/C1301/data/roadtrll.zip.

Okuyama, Y., 2009, _Impact Estimation Methodology: Case Studies_ , World Bank, mimeographed.

Phung, D. T. and Nguyen, P., 2008. Vietnam Household Living Standard Survey (VHLSS) 2002 and 2004: Basic Information. In: Nguyen, N and Hansen, H., ed. 2007. _Market, Policy and Poverty Reduction in Vietnam_ . Hanoi: Vietnam Culture and Information Publishing House. Annex.

- Rosenzweig, Mark, and Hans, Binswanger, 1993, Wealth, Weather Risk, and the Composition and Profitability of Agricultural Investments, _Economic Journal_ , 103‐416: 56‐78.

- Thomas, Timothy, 2009, _A Geographically Referenced Rainfall and Weather‐Related Shock Database for Vietnam_ , mimeographed.

Thomas, Timothy, 2010, _Controlling for Heteroskedasticy, Spatial Relations, and Clusters in Household Surveys_ , mimeographed.