rafmacalaba/datause-encoder-data huggingface dataset:
**Figure 10. Cross-border financial investments from and to LAC, by group of countries**

<!-- Start of picture text --> Panel A. LAC as Sender Panel B. LAC as Receiver<br>Portfolio Investments<br>180 12 700 12<br>160 10 600 10<br>140<br>500<br>120 8 8<br>100 400<br>6 6<br>80 300<br>60 4 4<br>200<br>40<br>20 2 100 2<br>0 0 0 0<br>2001-2005 2006-2011 2001-2005 2006-2011 2001-2005 2006-2011 2001-2005 2006-2011<br>To North and South To LAC From North and South From LAC<br>Syndicated Loans<br>4.5 1.8 80 1.8<br>4 1.6 70 1.6<br>3.5 1.4 60 1.4<br>3 1.2 1.2<br>50<br>2.5 1 1<br>40<br>2 0.8 0.8<br>1.5 0.6 30 0.6<br>1 0.4 20 0.4<br>0.5 0.2 10 0.2<br>0 0 0 0<br>1996-2000 2001-2005 2006-2011 1996-2000 2001-2005 2006-2011 1996-2000 2001-2005 2006-2011 1996-2000 2001-2005 2006-2011<br>To North and South To LAC From North and South From LAC<br>M&A<br>14 7 60 7<br>12 6 50 6<br>10 5 5<br>40<br>8 4 4<br>30<br>6 3 3<br>20<br>4 2 2<br>2 1 10 1<br>0 0 0 0<br>1996-2000 2001-2005 2006-2011 1996-2000 2001-2005 2006-2011 1996-2000 2001-2005 2006-2011 1996-2000 2001-2005 2006-2011<br>To North and South To LAC From North and South From LAC<br>Greenfield<br>8 12 100 12<br>7 90<br>10 80 10<br>6<br>8 70 8<br>5 60<br>4 6 50 6<br>3 40<br>4 30 4<br>2<br>2 20 2<br>1 10<br>0 0 0 0<br>2003-2005 2006-2011 2003-2005 2006-2011 2003-2005 2006-2011 2003-2005 2006-2011<br>To North and South To LAC From North and South From LAC<br>Brazil and Mexico LAC Top 5 (excluding Brazil and Mexico) Rest of LAC countries<br>Avg. Value (2011 Constant U.S. Dollars Billions) Avg. Value (2011 Constant U.S. Dollars Billions)<br>Avg. Value (2011 Constant U.S. Dollars Billions) Avg. Value (2011 Constant U.S. Dollars Billions)<br>Avg. Value (2011 Constant U.S. Dollars Billions) Avg. Value (2011 Constant U.S. Dollars Billions)<br>Avg. Value (2011 Constant U.S. Dollars Billions) Avg. Value (2011 Constant U.S. Dollars Billions)<br><!-- End of picture text --> This figure shows the yearly average investment from (to) LAC countries by region and group of LAC countries for portfolio investments, syndicated loans, M&A, and greenfield investments. The group “LAC Top 5 (excluding Brazil and Mexico)” includes Argentina, Chile, Colombia, Peru, and República Bolivariana de Venezuela. Panel A shows the investments from LAC countries. Panel B shows the investments to LAC countries. North countries are the G7 and Western Europe. South countries are all the others (excluding LAC countries). Offshore centers are excluded from the sample. Values are expressed in 2011 constant U.S. dollars. Investments from (to) North and South countries are measured in the left-hand side axes. Investments from (to) LAC countries are measured in the right-hand side axes.
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75
used when averaging.'<sup>0</sup> This may generate jumps in the composite index, though a closer inspection of the simple average shows that there is no significant bias in the final estimation."1

# RESULTS FOR THE LITHUAIANN CASE

The nine series selected, for their close relationship with the IEP, can be combined in several ways in the construction of the composite index. In this exercise a particular CLI is composed of the following variables: government lending funds in deposit money banks, interest rate of loans in litas 1-5 years (reciprocal), quasi-money, unemployment and real effective exchange rate. These variables appear to be effective in predicting recent movements in the reference series. It is important to note that these components are by no means definitive. Their relevance must be re-evaluated from time to time, based on their predictive ability. Series (other than the nine previously listed) must be examined to see if they present cyclical patterns that are consistent with the IIP cycle.'<sup>2</sup> Figure 1.1 presents the CLI and reference series estimated in December 1999.

**Figure 1.1 Composite Leading Indicator and UP, December 1999**

<!-- Start of picture text -->
1.4<br>1 .3<br>1 .2<br>0.8<br>0.7<br>CLI  ---- IIP<br><!-- End of picture text -->

**_'°_** _A linking factor_ is used to link an index with incomplete series to the body of the complete index. Its estimation involves applying the growth-rate of the incomplete index to the last point of the full index (see OECD, 1987).

" It must be kept in mind that the introduction of a linking factor may also generate a bias because of the risky assumption that the incomplete series follows the same growth pattern that the rest of the series. **12** In particular, for Lithuania it would be of great help to consider business survey data. These surveys of expectations of future trends have proven useful in other countries.

7
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37
# **1 Introduction**

Collecting accurate data on intimate partner violence (IPV) is difficult because of under-reporting by women, often due to the fear, stigma, and shame associated with IPV. It is especially challenging in face-to-face (F2F) interviews where the lack of anonymity can inhibit disclosure. While selfcompleted surveys offer more privacy, they are impractical when illiterate respondents are the target population. In low-income or rural settings, small homes increase the risk of family members overhearing conversations with enumerators, raising further ethical concerns about privacy and the potential for backlash from perpetrators. Nonetheless, ensuring accurate IPV disclosure is crucial to preventing and responding to IPV. It is especially important in experimental or quasiexperimental studies where the interventions themselves may affect disclosure of IPV, or where low rates of disclosure may undermine statistical power.

We addressed these issues by adapting existing measurement tools to better suit rural-poor settings. We also fielded two experiments, one to evaluate respondents’ comprehension of questions using these adapted tools, and the other to compare the impacts of face-to-face (F2F) enumerator-administered modules versus audio computer assisted interviewing (ACASI) on IPV reporting.<sup>1</sup> In the second experiment, we randomized at the respondent-level, whether they answered IPV-related questions via ACASI first, or F2F first.

We have two key findings. First, our experiments demonstrate that respondents comprehend ACASI well, despite high levels of illiteracy. By randomizing the order of the Likert-scale answer options corresponding to different frequencies of IPV, we found that reporting does not depend on the ordering of the response options. This is further reinforced by the fact that we found high agreement in responses to non-IPV questions when asked via ACASI or F2F.

Second, answering sensitive questions in private first increases IPV disclosure later. Specifically, we find that F2F reports of IPV are significantly higher for respondents who previously answered the same questions using ACASI. By contrast, we observe no similar impact for non-IPV questions which were first asked by ACASI and then repeated F2F. The continued higher reporting of IPV

> 1ACASI is a self-interviewing method where women listen to audio recordings of questions in the local language on headphones, allowing them to privately respond to questions using a touch screen on a tablet.

2
**18**

The discretionary stimulus packages announced by each country has mainly occurred over 2009 and 2010 and is usefully summarised by the OECD<sup>15</sup> . For the United States the cumulative stimulus is nearly 5 per cent of GDP and for China it is over 11 per cent of GDP. It is unlikely that such a stimulus will suddenly end in 2010 for two reasons: it is hard to crank up government spending on things like infrastructure quickly and governments usually find it hard to reign in spending quickly once programs are announced. Therefore, whilst assuming the same cumulative fiscal response as outlined by the OECD and other studies, the fiscal response has been assumed to taper off quickly after 2010 but finishing in 2012. The assumed fiscal response is outlined in table 3.7.

|3.7**The assumed fiscal policy response**per cent of GDP|
|---|

|**_Country/region_**|**_2009_**|**_2010_**|**_2012_**|**_2013_**|**_Cumulative_**|
|---|---|---|---|---|---|
|United States|2.07|1.55|1.04|0.52|5.18|
|Japan|1.46|1.10|0.73|0.37|3.65|
|United Kingdom|1.32|0.99|0.66|0.33|3.29|
|Germany|1.38|1.04|0.69|0.35|3.45|
|Euro area|1.30|0.98|0.65|0.33|3.25|
|Canada|1.68|1.26|0.84|0.42|4.20|
|Australia|2.48|1.86|1.24|0.62|6.21|
|Rest of OECD|1.00|0.75|0.50|0.25|2.50|
|China|4.80|3.60|2.40|1.20|12.00|
|India|0.50|0.38|0.25|0.13|1.25|
|Other Asia|2.00|1.50|1.00|0.50|5.00|
|Latin America|0.50|0.38|0.25|0.13|1.25|
|Other LDC|0.50|0.38|0.25|0.13|1.25|
|EEFSU|1.70|1.28|0.85|0.43|4.25|
|OPEC|3.00|2.25|1.50|0.75|7.50|

_Source:_ OECD 2009 and authors’ calculations.

# _Shock 6: Rise in trade and financial protectionism_

Rising trade protectionism is a real threat. It occurred during the Great Depression and is attributed with making matters far worse. The main driver for this protectionism was to protect jobs. The Smoot-Hawley legislation in the United States at the time of the

> 15 OECD 2009, _Fiscal Packages Across OECD Countries: Overview and Country Details_ , Paris, 31 March.
that there have not been many changes in the ranking, with Mozambique and Namibia still on the top of the list.7 A rapid comparison across regions reveals that Singapore had a FDI business indicator index twice as high as the best African country in 1995/1997. However, Ireland and Hungary were ranked about the same level as Senegal and Mauritius. This result may appear surprising at first sight, but one can observe that the flows of FDI were about the same in Senegal and Ireland, when compare to their respective GDP in 1997 (about 3.8 per cent) and Ireland has, in dollars, more natural resources than Senegal. It may also reveal some of the limits of our indicator when the differences in GDP are too big across countries - the assumption that FDI is perfectly elastic to changes in GDP might not be robust across region or countries with large differences in GDP levels.

Our ranking can be compared with those obtained in some well known surveys such as the International Country Risk Guide (ICRG) and the Institutional Investors (II) ratings that are reported in the second and third columns of table 2.8 If the ranking appears quite similar for a few countries,<sup>9</sup> there exist significant differences both at the top and bottom of the table. While South Africa, Zimbabwe, Kenya and Malawi appear in the bottom half of our ranking, they are on the top of the list for the two other indicators. On the other hand, Mali and Mozambique have not been ranked very high by the ICRG and II indexes but are among the most attractive countries according to our indicator. Io possibilities; Zambia has followed a relatively aggressive privatization programme and liberalization policy. 7 The 1998 ranking is incomplete because the data on FDI inflows are still missing for a few countries.

8 Unfortunately, the Competitiveness Indicator developed by the World Economic Forum is not available for most of the countries covered in this note. However, Namibia and Mauritius were also well ranked in their 1998 ranking, but South Africa was perceived as much more competitive, while Mozambique much less than reported in this note.

9 For example, Namibia has been traditionally perceived as a secure country, with satisfactory macroeconomic indicators, a good and reliable judiciary system and access to the large South African market. Similarly, the weak performance of Sierra Leone and Congo has been well publicized with their unstable political climate and multiple economic problems.

10 In fact, the coefficient correlation between our indicator and the ICRG and II indexes is negative for the period 1996-1997 (see more details in the next section).

7
||Source: Enterprise Surveys.<br>www.enterprisesurveys.org|
|---|---|
|Initial Employment (logs)|Log of total number of permanent full-time<br>workers at the firm in the initial year<br>(beginning of the growth period which is 2<br>fiscal years ago for most countries and 3 fiscal<br>years ago for other countries).<br>Source: Enterprise Surveys.<br>www.enterprisesurveys.org|
|Age of Firm (logs)|Log of age of the firm. The age of the firm is<br>defined as the year the Enterprise Survey was<br>conducted minus the year the firm first started<br>operations.<br>Source: Enterprise Surveys.<br>www.enterprisesurveys.org|
|Manager Experience (logs)|Log of the number of years of experience the<br>top manager of the firm has working in the<br>industry.<br>Source: Enterprise Surveys.<br>www.enterprisesurveys.org|
|Exports (proportion of sales)|The proportion of the firms’ annual sales made<br>abroad in the last fiscal year. Only direct<br>exports are included.<br>Source: Enterprise Surveys.<br>www.enterprisesurveys.org|
|Foreign Ownership (% ownership)|Percentage of the firm that is owned by<br>foreign individuals, companies or<br>organizations.<br>Source: Enterprise Surveys.<br>www.enterprisesurveys.org|
|Female Manger (dummy)|Dummy variable equal to 1 if the top manager<br>of the firm is a female and 0 otherwise.<br>Source: Enterprise Surveys.<br>www.enterprisesurveys.org|
|Multi-firm (dummy)|Dummy variable equal to 1 if the firm is part<br>of a larger parent firm and 0 otherwise.<br>Source: Enterprise Surveys.<br>www.enterprisesurveys.org|
|Power outages (logs)|Log of (1 plus) total hours of power outages<br>experienced by the firm in a typical month<br>over the last fiscal year.<br>Source: Enterprise Surveys.<br>www.enterprisesurveys.org|
|Informal Competition (dummy)|Dummy variable equal to 1 if the firm reported<br>competing against informal or unregistered<br>firms and 0 otherwise.|

49
serve significant changes for people with higher reservation wages (above 6,600 pesos). While the pattern of treatment effects is similar, the magnitude is much smaller and not significant.

The last piece of evidence in support of reservation wages as an underlying mechanism for the treatment effects comes from hourly wage data collected in the endline survey. Appendix Figure A2 shows how hourly wages evolve over the employment spell for participants with formal sector jobs. Compared to the control group, youths eligible for the wage incentive accept jobs that pay around 5 pesos (12%) less in the first few months (suggesting that they lowered reservation wages).

These results consistently suggest that reservation wages are binding for job seekers, which is in line with evidence from the U.S. by Krueger and Mueller (2016). It raises the question of why youths in our setting hold these high reservation wages in light of rapid skill and wage growth they would experience in formal employment. Next, we will explore the role of time preferences, false beliefs and liquidity constraints.

# **5.3 Discount factors**

One explanation for why job seekers set high reservation wages and search little for jobs in the formal sector relative to the informal sector is that they heavily discount future benefits of formal employment including strong wage growth and being covered by social security programs.<sup>27</sup> We elicit participants’ discount rates in two ways. First, as part of the inperson endline survey we use the traditional method of asking hypothetical choices between payments in one month or one year.<sup>28</sup> Second, we implement an incentive-compatible way to elicit time preferences for 665 respondents in our second endline survey. Specifically, respondents are invited to participate in a lottery. Their payout, if they win, is determined by their choices between receiving 2,000 pesos in one month or a larger amount in one year. We elicit time preferences through a set of binary choice questions and compute individual discount factors by dividing 2,000 by the amount at which they are switching to the payout 27Importantly, DellaVigna and Paserman (2005) show that in a search model with only one sector, higher time discount rates are associated with lower reservation wages since job seekers assign a lower value of future benefits of search. In our setting with two sectors, high discount rates lead job seekers to set high reservation wages for the formal relative to the informal sector since they discount the value of stronger future wage growth.

> 28By giving choices between one month and one year we elicit the longer term discount factor _δ_ rather than the short time discount factor _β_ . Letting participants choose between two future payouts also assuages concerns that choices are influenced by respondents’ mistrust about whether future transfers will take place.

31