rafmacalaba/datause-encoder-data huggingface dataset:
# **Data Appendix.**

## _(1). Dependent Variables_

Gini: Gini coefficients are from Deininger and Squire (1996).

LQ1 - LQ4: Lowest to highest quartile of the income share from Deininger and Squire (1996).

## _(2). Dummy Variables_

EASIA: 1 for East Asia, 0 otherwise.

LATIN: 1 for Latin America, 0 otherwise.

OECD: I for member countries, 0 otherwise.

### _(3). Predetermined Variables_

TOT: Terms of trade calculated by dividing export price (IFS line 76) by import price (IFS line 76.x). For those countries whose value is missing in IFS, we get the export price by dividing current export (import) of goods and non-factor services by 1995 constant price export (import) of goods and non-factor services in the World Bank database.

FIXK: Fixed capital formation to GDP (IFS line 99.b) measured by domestic public (and private) investment to GDP. This is used as a proxy for the manufacturing sector productivity since many developing countries do not have good data to estimate it.

LL: Liquid liability to GDP. Liquid liability equals currency plus demand and interest bearing liabilities of banks and other financial intermediaries.

17
Chernozhukov, V., Demirer, M., Duflo, E., & Fernández-Val, I. (2023). Fisher-schultz lecture: Generic machine learning inference on heterogenous treatment effects in randomized experiments, with an application to immunization in india.

- Cox, J. C., Kreisman, D., & Dynarski, S. (2020). Designed to fail: Effects of the default option and information complexity on student loan repayment. _Journal of Public Economics_ , _192_ (11). https://doi.org/https://doi.org/10.1016/j.jpubeco.2020.104298

- De Neve, J.-E., Imbert, C., Spinnewijn, J., Tsankova, T., & Luts, M. (2021). How to improve tax compliance? evidence from population-wide experiments in belgium. _Journal of Political Economy_ , _129_ (5), 1425–1463. https://doi.org/10.1086/713096

- Foster, J. C., Taylor, J. M., & Ruberg, S. J. (2011). Subgroup identification from randomized clinical trial data. _Statistics in Medicine_ , _30_ (24), 2867–2880. https://doi.org/10.1002/sim.4322

- Hahn, P. R., Murray, J. S., & Carvalho, C. M. (2020). Bayesian Regression Tree Models for Causal Inference: Regularization, Confounding, and Heterogeneous Effects (with Discussion). _Bayesian Analysis_ , _15_ (3), 965–2020. https://doi.org/10.1214/19-BA1195

- Hastie, T., Tibshirani, R., & Friedman, J. (2009). _The elements of statistical learning: Data mining, inference, and prediction_ . Springer. https://books.google.com/books?id=eBSgoAEACAAJ

- Hebous, S., Jia, Z., Løyland, K., Thoresen, T. O., & Øvrum, A. (2023). Do audits improve future tax compliance in the absence of penalties? evidence from random audits in norway. _Journal of Economic Behavior Organization_ , _207_ , 305–326. https://doi.org/https://doi. org/10.1016/j.jebo.2023.01.001

- Hill, J. L. (2011). Bayesian nonparametric modeling for causal inference. _Journal of Computational and Graphical Statistics_ , _20_ (1), 217–240. https://doi.org/10.1198/jcgs.2010.08162

- Imbens, G. W., & Rubin, D. B. (2015). _Causal inference for statistics, social, and biomedical sciences: An introduction_ . Cambridge University Press.

- Kirchler, E. (2007). _The economic psychology of tax behaviour_ . Cambridge University Press. Kleven, H. J., & Kopczuk, W. (2011). Transfer program complexity and the take-up of social ben-

- efits. _American Economic Journal: Economic Policy_ , _3_ (1), 54–90. https://doi.org/10.1257/ pol.3.1.54

27
otherwise be possible. Furthermore, restrictions on capital outflows mean that enterprise investment largely has been restricted to domestic projects.

In sum, the underdevelopment of the domestic financial system may help to explain the high rates of both savings and investment in China. The net impact on the current account is ambiguous in principle, because financial development could reduce both savings and investment rates. However, the cross-country empirical evidence indicates that domestic financial deepening lowers the savings rate and increases investment.<sup>22</sup> Especially in combination with an open capital account, it is plausible that higher-quality domestic financial intermediation could place greater downward pressure on savings than investment. In particular, the international capital funneled through domestic banks and domestic financial markets to high-return domestic projects may compensate for a reduction in investment in those inefficient enterprises that are protected by the current financial system. Moreover, a better financial system could stimulate consumption (by providing more credit) and reduce the need for maintaining high savings levels (either for precautionary motives or to finance future consumption).

# **III.b. India**

India suffered a severe financial crisis in the early 1990s, and that crisis subsequently led to a broad series of reforms. The goal was to spur Indian growth by fostering trade, FDI, and portfolio equity flows while avoiding debt flows that were perceived as potentially destabilizing. In the subsequent years, India has undergone extensive but selective liberalization, summarized in Table 5. Substantial capital controls, however, do remain in place.

The discouragement of external debt has restricted domestic entities’ ability to issue bonds on international markets and the entry of foreign investors to the domestic bond market. Moreover, the restrictions on purchases by foreigners in the corporate and government bond markets are much more stringent. Hence, the market for private bonds remains underdeveloped, as shown in Figure 10. The restrictions on external debt are heavily influenced by memories of India’s debt crisis in the early 1990s, with the composition of capital inflows subsequently shifting towards a much higher ratio of equity to debt flows.

By contrast, the approach to equity inflows has been much more liberal. Restrictions on FDI inflows have been relaxed progressively, although they still exist and India receives far less direct investment compared with China (Table 2a). The distinctive characteristic of equity flows into India, however, is not the direct investment, but rather the relatively high level of portfolio equity financing. India’s broad domestic institutional investor base has aided the entry of foreign institutional investors (FIIs) that are permitted to take partial stakes in equity of quoted Indian enterprises.

Capital outflows also are restricted, although the system is being liberalized (Patnaik and Shah 2006a.) In particular, Indian banks are not permitted to acquire external assets, but

> 22 See International Monetary Fund (2005).

12
||**Table 4: Effec**<br>|**ts of High an**<br>|**d Low Intern**<br>|**et Adoption**<br>||||
|---|---|---|---|---|---|---|---|
|VARIABLES|(1)|(2)<br>ln|(3)<br> (Total Export|(4)<br>s)|(5)|(6)<br>ln (Average<br>Value)|(7)<br>ln (Number of<br>products exported)|
|=1 if both high Internet adoption|0.0790***||||0.259***|0.196***|0.0626***|
||(0.0126)||||(0.0205)|(0.0179)|(0.0111)|
|=1 if exporter high and importer low Internet||||||||
|adoption||0.280***|||0.354***|0.118***|0.236***|
|||(0.0195)|||(0.0207)|(0.0172)|(0.0118)|
|=1 if exporter low and importer high Internet||||||||
|<br>adoption|||-0.287***||-0.0406*|0.132***|-0.172***|
||||(0.0228)||(0.0228)|(0.0191)|(0.0131)|
|=1 if both low Internet adoption||||-0.184***<br>(0.0165)||||
|GDP exporter (log)|0.409***|0.378***|0.395***|0.397***|0.367***|0.0643***|0.302***|
||(0.0155)|(0.0155)|(0.0158)|(0.0152)|(0.0153)|(0.0114)|(0.0104)|
|GDP importer (log)|0.0952***|0.0875***|0.105***|0.0836***|0.0861***|0.0729***|0.0132|
||(0.0144)|(0.0143)|(0.0148)|(0.0142)|(0.0140)|(0.0107)|(0.00940)|
|Observations|221,581|221,581|221,581|221,581|221,581|221,581|221,581|
|R-squared|0.859|0.860|0.860|0.859|0.860|0.696|0.863|
|Year FE|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Country-pair FE|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Standard errors are clustered at the country-pair.||||||||
|*** p<0.01, ** p<0.05, * p<0.1||||||||

9
**Table** **<u>5: Trade, tariff rates and differentiated products.</u>**

||(1)|(2)|(3)|(4)|(5)|(6)|
|---|---|---|---|---|---|---|
||||_Trade_<br>|_Gap_<br>|||
|Tariff|0.012|0.006|0.007|0.012|0.005|0.006|
||(0.001)***|(0.001)***|(0.001)***|(0.001)***|(0.001)***|(0.001)***|
|Tariff*Conservative||0.015|||0.016||
|dummy||(0.002)***|||(0.002)***||
|Tariff*Liberal dummy|||0.014|||0.015|
||||(0.002)***|||(0.002)***|
|Conservative dummy||-0.009<br>(0.03)|||0.009<br>(0.032)||
|Liberal dummy|||0.015|||0.032|
||||(0.029)|||(0.03)|
|Agricultural products|Included|Included|Included|Excluded|Excluded|Excluded|
|Observations|132408|132408|132408|127893|127893|127893|
|Adjusted R-squared|0.59|0.59|0.59|0.59|0.59|0.59|

All regressions include country-year fixed effects and a constant. Standard errors, clustered on 6-digit product, are listed in parentheses. * significant at 10%; ** significant at 5%; *** significant at 1%.

As a robustness check, we introduce country-year fixed effects together with 6-digit product fixed effects thus controlling for country-specific changes in the performance of the customs service as well as unobservable product characteristics (see Table 6). The estimated coefficient of the interaction term is still positive and statistically significant at the 1% level in all specifications, both with and without agricultural products and both for the liberal and the conservative definition of differentiated products. The estimated elasticity of the trade gap with respect to the tariff rate is positive and significant in 4 out of 6 specifications.

15
A primary function of financial markets and the financial system is to pool and diversify risk. In recent years a range of financial innovations has emerged with the potential to improve household risk management, including housing futures based on Case-Shiller price indices (Shiller, 2008), prediction markets linked to economic and political events, and index insurance products designed for hedging weather, price and other agricultural risks.

We are not the first to document demand for insurance that is inconsistent with standard rational models. David Cutler and Richard Zeckhauser (2004), writing that “financial markets, despite their vast resources and wide participation, are not a major bearer of large private risks,” highlight the fact that many consumers pay high premiums for insurance on consumer durables, but remain uninsured against much more significant risks such as permanent disability. While informational frictions are an important source of insurance market failure in many contexts<sup>22</sup> , in our setting households are unlikely to have significant private information about insurance payoffs, given that rainfall is exogenous and publicly observable.

The micro-insurance industry is still in its infancy. Insurance providers are experimenting with different contract features to learn the best ways to attract customers and create useful products (e.g. see Giné et al. (forthcoming) for a description of the rainfall insurance sector in India). From our empirical results, we draw a number of tentative conclusions about factors that may help increase demand for the rainfall risk management product and improve the welfare benefits of the policies.

First, the importance of liquidity constraints and high measured discount rates amongst our sample suggests that policies should be designed to provide payouts as quickly as possible, especially during the monsoon season when households appear to be particularly credit constrained. For example, payouts from a policy covering the first phase of the monsoon, if paid immediately, could be used by farmers to help fund crop replanting later in the monsoon season. In practice to date, payouts have not been made until after the end of the monsoon, in part because of delays in receiving certified rainfall data from government rainfall stations. Over time, ICICI Lombard has begun using automated rain gauges that allow them to measure rainfall immediately; this in principle should allow payouts to be made more quickly, and by increasing

> 22 The role of adverse selection and moral hazard in insurance markets has been the subject of a very large literature, see for example Pierre-André Chiappori and Bernard Salanié (2000), Amy Finkelstein and Kathleen McGarry (2004), Hanming Fang, Michael Keane and Dan Silverman (2008), John Cawley and Tomas Philipson (1996) and Michael Rothschild and Joseph Stiglitz (1976).

23
influence the provincial government to create a business-friendly environment. However, this effect would have been captured by the various PCI modules that measure the ability of the provincial government. Other possible reasons point towards the externalities and spillover effects of having large firms in the province. Large firms can attract more specialized labor and can create knowledge spillovers, generating Marshallian externalities for firms in that province. These large firms might have vertical linkages with the local firms, causing these firms to be more productive.

Our results contrast significantly with McCulloch et al. (2013). While their results are not directly comparable as the dependent variable is investment levels, McCulloch et al. (2013) find that the business environment does not have any effect on firm investments. The only PCI module that does have a significant effect on firm investment is the transparency measure, which captures the amount of information the firm can obtain from the provincial government. The difference in results may be attributed to the different constructions of the PCI indices. While McCulloch et al. (2013) took the PCI data as is from the source, we were more circumspect in selecting survey questions that are consistently present in the time period and questions that are within the control of the provincial bureaucracy due to our focus on local governance.

**Table 4: Regression Results with All PCI sub-indices**

||<br>Labor productivity|Log(LP TFP)|
|---|---|---|
|Entry|0.515|0.018*|
||(0.534)|(0.010)|
|Land|0.612**|0.012*|
||(0.269)|(0.007)|
|Transparency|-0.179|-0.000|
||(0.703)|(0.011)|
|Time|1.262**|0.008|
||(0.566)|(0.010)|
|Informal charges|0.821**|0.018**|
||(0.364)|(0.009)|
|Proactive|0.054|-0.001|
||(0.304)|(0.008)|
|Labor|-0.221|-0.005|
||(0.317)|(0.006)|
|Legal|0.815**|0.009|
||(0.396)|(0.007)|
|Share of large firms in|-0.177**|0.002**|
|province|||
||(0.088)|(0.001)|
|Capital intensity ln(K/L)|3.268***|-0.161***|
||(1.180)|(0.036)|
|Firm size (ln employment)|-15.433***|0.013|
||(2.708)|(0.057)|
|Constant|55.956***|3.731***|

12
# **Figure B4: Aluminum**

<!-- Start of picture text --> Log scale<br>9.0<br>Log price Permanent component<br>8.5<br>8.0<br>7.5<br>7.0<br>1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020<br>Source : Authors’ calculations<br><!-- End of picture text --> <!-- Start of picture text --> Log scale<br>0.75<br>Medium-term cycle Transitory component<br>0.50<br>0.25<br>0.00<br>-0.25<br>-0.50<br>1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020<br>Source : Authors’ calculations<br><!-- End of picture text --> _— 45 —_
Table 3: Impact of Ruling Party Status on Non-Federal Roads, RD Estimates

||LLR w|ith bandw|idth <sup>ˆ</sup>_h_|Polyn|omial of or|der_p_|
|---|---|---|---|---|---|---|
||ˆ_h_1= .3|ˆ_h_2= .2|ˆ_h_3= .1|<br>_p_= 2|<br>_p_= 3|<br>_p_= 4|
||(1)|(2)|(3)|(4)|(5)|(6)|
|A. Two-lanes|||||||
|President|0.016|0.113|-0.198|-0.059|0.009|0.116|
||(0.169)|(0.215)|(0.289)|(0.152)|(0.208)|(0.250)|
|Observations|5,017|3,436|1,777|9,084|9,084|9,084|
|R-squared|0.059|0.102|0.164|0.059|0.059|0.059|
|B. Divided|||||||
|President|-0.038|0.102|0.513|-0.018|0.051|0.115|
||(0.206)|(0.258)|(0.362)|(0.204)|(0.245)|(0.287)|
|Observations|4,927|3,361|1,742|8,989|8,989|8,989|
|R-squared|0.160|0.180|0.198|0.112|0.112|0.113|
|C. Other pave|ment||||||
|<br>President|<br>-0.309|-0.175|-0.091|-0.144|-0.228|0.115|
||(0.391)|(0.481)|(0.795)|(0.382)|(0.482)|(0.597)|
|Observations|4,233|2,884|1,460|7,763|7,763|7,763|
|R-squared|0.171|0.208|0.238|0.154|0.154|0.154|
|Covariates|Yes|Yes|Yes|Yes|Yes|Yes|
|Fixed Effects|Yes|Yes|Yes|Yes|Yes|Yes|

_Notes:_ The table shows the regression discontinuity estimates of the presidential party status in legislative elections on two-lane road (panel A), divided road (panel B) and other paved road (panel C) outcomes. The estimation methods include: local linear regression in columns 1-3 with two MSE-optimal bandwidth choices ( _h_<sup>ˆ</sup> 1 and _h_<sup>ˆ</sup> 2) and one CER-optimal bandwidth choice ( _h_<sup>ˆ</sup> 3), calculated according to Calonico et al. (2017); spline polynomial approximation in columns 4-6 with second, third, and fourth polynomial, respectively. Covariates include state capital dummy, US border dummy, log area size, log population size, and proxies for higher education and employment. Robust standard errors clustered at the municipality level are reported in parentheses. All specifications include state, time, and state-interacted-with-time fixed effects. ** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1.

cutoff between constituencies that favor the president’s party and those where the opposition is successful. Table 3 presents the RD estimates of the president’s party effects on differences in two-lane roads (panel A), divided roads (Panel B), and other types of paved roads (panel C). Although we use similar specifications as in Table 2, we only report the estimation results including the relevant covariates and fixed effects. We also report both the local linear and polynomial regressions with the previously defined op17
22 trade association. Moreover, the average rating of the value of the services of the two sets of suppliers was virtually identical.

- The Indonesian experience offers three lessos one cautionary, one niixed and one hopeful.- The cautionary lesson concerns the role of centralized export institutions. Like many - other developing countries, Indonesia erected in the 1970s two elaborate export institutions NAFED, whose prime responsibility is to promote trade fairs with Indonesian participation, and the Iternational Trade Promotion Center, an international network- of commercial offices located in Indonesian embassies abroad. Yet by 1985, fairs aside, the perception was widespread that these insftituons were of limited usefulness.

-

The mixed lesson concerns the role of industry associations. Parts of Indonesia's furniture and garment associations emerged in the firm surveys as useful sources of collective support. Yet in general Indonesia's industry associations tend to be exceedingly weak. They are not professionally staffed; they are rarely accountable to their members; they tend to be' captured by powerful players in their industries; and their umbrella organization lacks credible autonomy from government. As the country study makes clear, it will be no simple matter to re-orient a substantial number of the country's industry associations to play a constructive promotional role .......

The hopeful lesson concerns the experience of the Export Support Board, created in 1985 in response to the perception of filure of the exisdng export institutions. The ESB represents an intriguing departure from the institutional model adopted earlier in that its role was to finance marketing support, not deliver it directly: it provided partial subsidies to nascent exporters who sought to participate in trade fairs abroad, to develop export promotional material, and (as discussed farther under the rubric of technical support systems) to employ technical consultants from abroad. Its complement of professional staff never exceeded 10 persons, yet its services were more widely used, and were rated more highly among the firms surveyed, than those provided by the elaborate, central export edifices.
# **3 Data, Calibration, and Shocks**

## **3.1 Data Sources**

Our data construction process follows steps similar to those in RUV but uses 2019 as the base year (whereas in RUV the base year is 2000). A summary of the data-construction B. process is provided here, with additional details available in Appendix _Labor, input, and consumption shares:_ Data from the BEA (for U.S. states) and from ICIO (OECD’s Inter-Country Input-Output Database) is used to compute the value-added share in gross output (which is used as the labor share in the model) and the input-output coefficients for each region. Consumption shares can be inferred based on trade flows, labor shares, and intermediate input shares.

_Bilateral flows:_ The model requires bilateral trade flows in all sectors between any pair B.2. of regions in the sample. These are constructed in 4 steps outlined in Appendix _Labor flows across sectors and regions:_ Data for intersectoral mobility for each U.S. state is obtained from the Current Population Survey (CPS), while frictionless mobility is assumed for other countries. In the extension allowing for migration within the U.S., data for interstate mobility is obtained from the American Community Survey (ACS).

_Labor supply:_ Data on employment by sector (including home production) comes from the WIOD Socio Economic Accounts, the International Labor Organization, the U.S. Census, and the ACS. As in RUV, only observations for people aged between 25 and 65 are kept. Labor force participation is measured as the share of individuals in that age group who are either employed or unemployed.

## **3.2 Parameter Calibration**

Table 1 describes the parameters used in the baseline specification. Notice that _γ_ (the nominal growth rate of world GDP in U.S. dollars) and _δ_ (the downward nominal wage rigidity parameter) are not separately identified. For a given _δ_ , if _γ_ is higher, then the DNWR is less likely to bind. Likewise, for a given _γ_ , if _δ_ is lower, then the DNWR is less likely to bind. Therefore, we require a normalization and set _δ_ = 1, indicating that nominal 10