rafmacalaba/datause-encoder-data huggingface dataset:
# **Chart 2**

<!-- Start of picture text --> Serious Delinquencies: FHA Outperforms Subprime<br><!-- End of picture text --> <!-- Start of picture text --> 25.0<br>Subprime ARM<br>20.0<br>15.0<br>10.0<br>5.0<br>FHA ARM All FHA<br>0.0<br>Source: Mortgage All Prime Subprime ARM All Subprime FHA ARM All FHA<br>Bankers of America<br>1Q02 2Q023Q02 4Q021Q032Q033Q034Q031Q042Q04 3Q044Q04 1Q052Q053Q054Q051Q062Q063Q064Q061Q07 2Q073Q07 4Q07<br>Pct Loans 90+ Del. & In Foreclosure<br><!-- End of picture text -->

# **The primary cause of subprime ARM defaults has been weak underwriting., in**

**large part by non-bank lenders.** Between 40 and 50 percent of subprime loans were made by independent non-bank lenders between 2004 and 2006 (Avery, et al 2007). Nonbank lenders such as New Century Financial aggressively pursued the “originate to distribute business model,” where it originated loans for sale to the capital markets. Founded in 1995, by the end of 2006 New Century was the third largest subprime lender in the country, with loan production that year of $51.6 billion. New Century filed for bankruptcy protection in April, 2007, primarily as a result of insufficient capital to satisfy demands from investors to repurchase defaulted and deficient mortgages. According to the bankruptcy court examiner, New Century had a “brazen obsession with increasing loan originations without due regard to the risks associated with that business strategy.” The primary consideration for loan quality was the ability to sell in the secondary market. More than 70 percent of loans originated by the company had low initial teaser rates, and 40 percent were underwritten on a stated income basis. New Century made frequent exceptions to its underwriting guidelines for borrowers who might not otherwise qualify for a loan. Early payment defaults, a sure sign of weak underwriting, rose from 4.38 percent of loans made in 2003 to 13.1 percent of loans in early 2007.<sup>6</sup> (Missal, 2008).

> 66 An early payment default is defined as a default on a loan in any of the first three months of its life.

5
<u>Table 3: Policy intervention/shock-NAFTA liberalization+elimination of PROCAMPO Using the CGE Model Simulation Results for Mexico</u>

|<br>**Impact on**|<br>**North**|<br>**Central**|<br>**Southwest**|**Southeast**|**Rio Bravo**|
|---|---|---|---|---|---|
|Household income<br>(urban)||||||
|Household income<br>(rural)||||||
|**Comments**|This simul<br>with elimin<br>by 10% of<br>impact of a<br>subsidies a<br>reflected in<br>simulated.<br>equally dis<br>not across<br>and Center<br>incomes in|ation combi<br>ating PRO<br>the gross v<br>combined<br>re similar in<br>rural hous<br>The drop in<br>tributed acr<br>regions. Th<br>regions suf<br>creases acro|nes the effect o<br>CAMPO incom<br>alue of their mai<br>NAFTA and re<br>general, the on<br>eholds‘ income<br>rural househol<br>oss household t<br>e RBB region s<br>fer the most. In<br>ss all regions an|f NAFTA trade<br>e transfers to m<br>ze production.<br>moval of ProC<br>ly important dif<br>drop when PR<br>ds‘ income is m<br>ypes (poor, med<br>uffesrs the least<br>contrast urban<br>d household ty|liberalization<br>aize producers<br>While the<br>AMPO<br>ference is<br>OCAMPO is<br>ore or less<br>ium, rich), but<br>and the North<br>household<br>pes.|

Source: Dinar and Asad (2006) Note: See note to Table 2.

Table 4: Policy intervention/shock-NAFTA+reduction of 50% in water supply for irrigation Using the CGE Model Simulation Results for Mexico

|**Impact on**|**North**|**Central**|**Southwest**|**Southeast**|**Rio Bravo**|
|---|---|---|---|---|---|
|Land Use(Fruits and<br>vegs)||||||
|Land Value (other<br>crops)|<br>|<br>|<br>|<br>|<br>|
|Household income||||||
|**Comments**|This simu<br>openness<br>NAFTA i<br>slightly dif<br>in crop an<br>of combin<br>policy res<br>compared<br>Employm<br>maize acr|lation addres<br>for water sca<br>s simulated.<br>fer. Drops<br>d other com<br>ed NAFTA<br>ults in reduct<br>to increase<br>ent increases<br>oss all region|ses the issue of<br>rcity. The impa<br>However, the m<br>in crop prices ar<br>modities prices<br>and water supp<br>ion in price of f<br>(5%) in price in<br>in fruits and ve<br>s. In other crop|compensation o<br>ct are the same<br>agnitudes of the<br>e more moderat<br>are more moder<br>ly reduction. Th<br>ruits and vegeta<br>the case of NAF<br>getables and de<br>s the impact is|f trade<br>as when just<br>impacts<br>e and increase<br>ate in the case<br>e combined<br>bles (1.5%)<br>TA alone.<br>creased for<br>differential.|

Source: Dinar and Asad (2006) Note: See note to Table 2.

48
13

**Figure 5** : _FDI per capita in Bulgaria, Romania and CEEC-8 population weighted average in 1990-2003 (in US dollars)_

<!-- Start of picture text --> 250<br>Romania<br>200<br>150<br>Bulgaria<br>100<br>CEEC-8<br>50<br>w eighted<br>average<br>0<br>1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003<br>(FDI per capita)<br><!-- End of picture text --> Source: IMF balance of payments statistics, EBRD data for data missing in the IMF statistics, and Bulgarian national statistics. Data for 2003 include the upward revision (48%) of the BCB (see the footnote below).

The contradiction is more apparent than real. Consider first that countries bordering the EU-15 (except those bordering Greece) have also moved fast in transition to competitive markets. In consequence, proximity has also somehow influenced the pace of transition, although the presence of potential foreign investors also probably had an influence on reforms. Second, richer countries are, to paraphrase Fisher, Sahay and Vegh (1998), closer to Brussels. Richer countries have also better institutions and are thus more attractive to FDI. Third, openness to trade influences the extent to which domestic markets are competitive. Contestability of domestic markets, in turn, reduces the extent to which distortions might affect the developments in unit labor costs. Both EBRD-based indicator and governance indicator indirectly captures contestability of domestic markets and thereby developments in unit labor costs.

While policy makers cannot do much about the size of a market or proximity to the EU, they can do quite a lot in designing institutions and changing policies. The latter also usually influence both unit labor cost and openness to trade and thus boost country’s attractiveness to foreign investors. More importantly, there is evidence that institutional quality towers over other determinants of FDI location. Campos and Kinoshita (2003) examined three groups of determinants: The first group comprised cost of labor, the size of domestic market, skills of labor, quality of infrastructure, and proximity to EU markets. The second group included institutions, macroeconomic policy and other policies that facilitate conduct of business. The third group related to agglomeration economies, i.e., new investors following decisions made by earlier investors to take advantage of positive spillovers related to knowledge spillovers, and availability of specialized labor and intermediate inputs. Their main finding was that institutions and agglomeration economies explain directions of FDI flows to transition economies—taken together they outweigh other determinants related to labor costs, proximity to EU markets and size of domestic market.

Recently observed increases in FDI inflows into Bulgaria accompanied by perceptible improvements in the quality of governance and market-supporting institutions appear to corroborate this finding. It also reinforces the policy message about the importance of staying the reform course and suggests that recently observed increase in FDI inflows would generate positive spillovers attracting new foreign investors in the future.
_Table A4.2. Attrition in Administrative Data_

||Has GPA, Medium-Run|Has GPA, Long-Run|
|---|---|---|
||(2016/2017 Q1+Q2)|(2016/2017 Q3+Q4)|
||(1)|(2)|
|Pre-Treatment GPA|0.004|0.009***|
||_(0.003)_|_(0.002)_|
|Treatment 1 “Student Self-Learn-|||
|ing"|-0.016|0.035**|
||_(0.017)_|_(0.017)_|
|Treatment 2 “Teacher Delivery”|0.004|0.053**|
||_(0.018)_|_(0.021)_|
|Age 12|0.010|-0.019**|
||_(0.010)_|_(0.008)_|
|Age 13|0.000|-0.018|
||_(0.013)_|_(0.014)_|
|Age 14|-0.060***|-0.107***|
||_(0.022)_|_(0.022)_|
|Female|-0.004|-0.004|
||_(0.003)_|_(0.003)_|
|Sixth Grader|0.010|0.013|
||_(0.014)_|_(0.018)_|
|Albanian|-0.081**|-0.042***|
||_(0.038)_|_(0.012)_|
|Roma|-0.073***|-0.099**|
||_(0.021)_|_(0.039)_|
|Other|-0.001|-0.013|
||_(0.014)_|_(0.016)_|
|N|33,454|33,454|
|N Control|12,426|12,426|
|N Treatment 1|10,995|10,995|
|N Treatment 2|10,033|10,033|
|_R2_|0.088|0.106|

* p < 0.05, ** p < 0.01, *** p < 0.001

_Notes:_ All regressions control for pre-treatment outcomes, demographic controls (including dummies for age, gender, academic year, and ethnicity), and municipality fixed effects. Robust standard errors are clustered at the school level in parentheses. All figures are rounded to three decimal places. _Source:_ Administrative data, school year 2016-2017, own calculations.

41
# _Some New Estimates of the Effect of Trade on Growth_

We now present some new results on the effect of trade on growth, relying on an existing methodology that has not been widely applied to this particular question but is quite useful in light of the problems discussed above. Our empirical strategy is simple. Rather than rely on cross-country differences in trade and growth to identify the effects of trade, we rely on the within-country variation in the data. In particular, we examine whether _changes_ in decadal average growth rates can be explained by changes in trade volumes.

Consider the following "standard" cross-country growth regression:

# (1) Yct = o + 1 YC,tk + 02'Xct + Tc + Yt + Vct

where yc, is log- level of per capita GDP in country c at time t, YC,t-k is its lag k years ago (k= 10 years in our application using decadal data) and X,, is a set of control variables which are measured as averages over the decade between t-k and t. We include trade volumes (exports plus imports as a share of GDP) among the variables in X. Subtracting lagged income from both sides of the equation gives the more conventional formulation in which the dependent variable is growth, regressed on initial income and a set of control variables. The disturbance term in the regression consists of an unobserved country effect that is constant over time, **l1,,** an unobserved period effect that is common across countries, **yt,** and a component that varies across both countries and years which we assume to be uncorrelated over time, vc, Most of the empirical growth literature considers growth over a very long period _(k=25_ years or more) so that there is only one observation per country. As a result, all of the effects of interest are estimated using only the cross-country variation in the data. Some papers consider shorter periods such as decades or quinquennia, and typically combine the cross-country and within-country variation in the data in a fairly ad-hoc manner. Caselli, Esquivel and Lefort (1996) provide a useful critique of conventional panel growth econometrics and a proposed solution. In this paper we adopt their preferred estimation strategy, which is to estimate equation (1) in differences, using appropriate lags of the righthand side variables as instruments. In particular, they advocate estimating the following regression: (2) Yct - Yctt-k = **(Yc,t-k** - Yct-2k )+ 2 '(Xct - Xct-k )+ (Yt - Yt-k )+ (Vct - Vc,t-k) 16
- 29 -

Bolivia's ill fated effort to introduce<sup>a value added</sup><sup>**tax**</sup> in 1976 provides the beet illustration<sup>of this lesson.</sup> Few resources were committed to educating<sup>the public on how a VAT</sup> operates, to creating an administrative<sup>apparatus to deal</sup> effectively with its implementation and to a careful designing of the tax forms. Not surprisingly,<sup>the new sales</sup> tax failed to live up to its promise. The much more successful reforms introduced in Jamaica,<sup>Indonesia and, more</sup> recently, in Malawi all benefitted<sup>from detailed and careful</sup> planning and preparation pius close<sup>monitoring after their</sup> implementation.

7. Good data and a reliable empirical<sup>analysis of the effects of</sup> the pre- and post-reform systems<sup>are vital prerequisites to</sup> convincing doubters of the soundness<sup>of proposed tax changes.</sup> Successful tax reform measures ordinarily<sup>require a detailed</sup> knowledge of the defects of the<sup>current system, particularly</sup> a sense of who pays taxes at the industry,<sup>firm and household</sup> level. They also require a feeling<sup>for how the distribution</sup> of tax burdens will be affected<sup>by tax measures that are</sup> supposed to make matters better. The recent tax reform erforte in Jamaica, Colombia, Malawi<sup>a.d Indonesia all</sup> display this attribute. The margin,.l effective tax rate methcdology is also increasingly **being** applied to measure the allocative impact of different tax<sup>policies.</sup>
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40
rates and wages of refugees and IDPs in the long term and when combined with other interventions (Schuettler and Caron, 2020). The training needs to be adapted to labor demand in the location where those forcibly displaced reside. It also must take into account the aspirations of the target group, as well as the legal framework that affects their access to the labor market. In terms of other active labor market policies, job matching and counseling interventions have shown positive results for refugees in high-income countries (Aslund and Johansson, 2011; Battisti et al., 2019; Joona and Nekby, 2012). The limited evidence for low- and middle-income countries is less clear (Caria et al., 2020). The same is true for wage subsidies (Clausen et al., 2009; Heinesen et al., 2013).

# **4.2.2 Rights granted to refugees and IDPs**

In an attempt to control the flow and composition of refugees seeking protection on their own territories and manage the actual or perceived negative externalities stemming from an influx of migrants, governments have often chosen to curtail the rights of refugees. In some countries, the rights of IDPs have been limited as well. While de jure refugee and asylum policies have become more restrictive in high-income countries over time, they have become more liberal in low and middle-income countries since the 1950s (Blair et al., 2021).<sup>5</sup> .

The welfare cost of these measures can be assessed when they are rescinded. Providing Venezuelans with a legal resident status increased their consumption and income and decreased their food insecurity compared to those residing irregularly in Colombia (Ib ́anez et al., 2022). Evidence from high-income countries shows positive impacts from limiting or shortening employment bans for asylum seekers (Marbach et al., 2018; Slotwinski et al., 2019) and reducing wait time for recognition of refugee status (Hainmueller et al., 2016; Hvidtfeldt et al., 2018), as well as a positive correlation between acquiring citizenship and better economic outcomes (Bakker et al., 2014; Bevelander and Pendakur, 2006; Govind, 2021). At the same time, results for policies to disperse populations of refugees geographically within high-income countries consistently show that not allowing refugees freedom of movement and settlement has negative impacts on their economic outcomes (Aksoy et al.,

> 5The results are from the Developing World Refugee and Asylum Policy (DWRAP) data set, which covers de jure policies in 92 low- and middle-income countries from 1952 to 2017

14
The Philippines illustrates the application of more detailed earmarking rules. Republic Act no. 7227 authorized the sale of land in Metro Manila military compounds formerly used as US military bases. The first land sale, of Fort Bonifacio, realized roughly US$800 million. Act 7227 specified how revenues realized from the sale of land in military compounds was to be used: 50% was to be invested in infrastructure to develop Special Economic Zones at other former US military sites; 32.5% was to be used for modernization of military equipment and housing for military personnel; 4% was dedicated to provision of housing for the homeless; 2.5% was allocated to the three municipalities within Metro Manila most affected by redevelopment of Fort Bonifacio; and 10% was to be contributed to the general budget of the national government.

It is difficult to track the ultimate impact of these revenue allocation rules. Revenues are fungible once they enter the budget process. The clearest connection can be established when earmarked land revenues finance the bulk of local infrastructure investment. Analysis of local infrastructure spending in Ethiopia reveals that investment expenditures fluctuate closely in line with receipts from land leasing. The constitutional earmarking of land revenues to infrastructure investment seems to have had the desired effect of significantly increasing local infrastructure spending, especially on road and water systems. Urban infrastructure investment in China has surged in line with revenues from land leasing. It is universally acknowledged that up to now essentially all locally financed infrastructure investment in China’s cities has been financed by land leasing, either directly or by using land leasing proceeds to service bank borrowing and municipal bonds.

There has been considerable controversy in the Philippines as to whether the earmarking provisions of Act 7227 have been applied appropriately. Funds from land sale go into the consolidated fund and are allocated as part of the government budget process. Exact tracking of the use of funds from land sales is impossible. However, all of the expenditure purposes identified in Act 7227 have been supported, indicating that earmarking rules have had an impact on expenditures, at least at a broad level.

On occasion, earmarking rules have had perverse effects. The Little Hoover Commission of the State of California concluded that the rules dedicating all revenues from agency property sales to debt service in the consolidated fund had the effect of discouraging agencies from identifying surplus properties. It recommended that agencies identifying surplus property share in the proceeds of sale, as an incentive to active participation in property disposition. As matters now stand, the Commission found, agencies do not even fully report their property holdings to the state inventory system, out of fear that their properties will be identified as surplus and sold without any benefit to the agency.

36
A Road to Trust educated individuals (those with secondary school education) are more likely to trust more. We do not find such an effect on individuals with some college education. This might be due to the small proportion of such individuals in our sample.

# **_6. Conclusion_**

In this paper, we provide evidence that road construction is associated with increased trust levels. Using panel data on 135 communities in the Philippines, we show that in villages in which a road was built over the period 2003-2006, trust increased by 4.5 percentage points. The magnitude of this coefficient is quite large given the very low levels of generalized trust in the Philippines. Further, our household-level results suggest that this impact manifests through increased interactions with people outside the community. In our setting, reduced transaction cost ( _i.e._ , road construction) are likely to lead to an increase in face-to-face interactions.

Finally, our results suggest that the current literature on the positive impact of trust on growth might have overlooked the potential endogeneity of trust. Indeed, reduced transaction costs promote growth and our results indicate that they also build trust. Further research is needed to understand if higher trust comes from economic growth (generated by reducing transaction costs) or comes directly from reduced transaction costs.

16
Change Mitigation? Evidence of Values, Preferences and Carbon Savings from a Choice Experiment in Ethiopia. World Bank Policy Research Working Paper 8499 (June).

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- Mørkbak, M.R., and Olsen, S.B. (2014) A Within-Sample Investigation of Test-Retest Reliability in Choice Experiment Surveys with Real Economic Incentives. _Agricultural and Resource Economics_ 59, 375-392.

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16