rafmacalaba/datause-encoder-data huggingface dataset:
Moenius, J (2000), _Three Essays on Trade Barriers and Trade Volumes._ Ph.D. dissertation, University of California, San Diego.

Moenius, J. (2004), Information versus Product Adaptation: The Role of Standards in Trade, Mimeo, Kellogg School of Management, Northwestern University, February.

Morrissey, O. (1991), “An evaluation of the economic effects of the aid and trade provision”, _Journal of Development Studies_ , 28(1): 104-129.

> Morrissey, O. (1993), ‘The Mixing of Aid and Trade Policies’, _The World Economy_ , 15, 69–84.

Nelson, D and S.J. Silva (2008) “Does Aid Cause Trade: Evidence from an Asymmetric Gravity Model’ WP 2008/21 University of Nottingham Leverhulme Center Nilsson, L. (1997), EU and Donor Exports: the Case of the EU countries, Essays on NorthSouth Trade, _Lund: Lund Economic Studies_ , 70, chap 3.

OECD (2005) “The Economic Impact of Trade Facilitation” TD/TC/WP(2005)12/Final. OECD (2006) Aid for Trade: Making It Effective. Organization for Economic Cooperation and Development, Paris.

Otsuki, T., Wilson, J. S., and Sewadeh, M. (2001). Saving two in a billion: Quantifying the trade effect of European food safety standards on African exports. _Food Policy_ , 26, 495–514.

Osei, R., Morrissey, O. and Lloyd, T. (2004). “The nature of aid and trade relationships”, _European Journal of Development Research_ , V. 16(2), pp. 354-374.

- Rajan, R.G. and A. Subramanian (2005a) “Aid and Growth: What Does the CrossCountry Evidence Really Show?” NBER WP 11513.

Rajan R.G. and A. Subramanian (2005b) “What Undermines Aid’s Impact on Growth?” IMF WP/05/126.

- Radelet, S. M. Clemens, and R. Bhavnani. (2005) “Aid and Growth”, _Finance and Development,_ vol 42:3, September

Radelet, Steven, Michael Clemens, and Rikhil Bhavnani. 2006. “Aid and Growth: The

- Current Debate and Some New Evidence.” In The Macroeconomic Management of Foreign Aid: Opportunities and Pitfalls, ed. P. Isard, L. Lipschitz, A. Mourmouras, and B. Yontcheva, 43–60. Washington, DC: International Monetary Fund.

- Santos Silva, J.M.C. and Silvana Tenreyro, 2006, “The Log of Gravity”, _Review of Economics and Statistics_ , 88(4), 641-658.

- Soloaga I., J.S. Wilson, and A. Mejia (2006) Moving forward faster: trade facilitation reform and Mexican competitiveness, _World Bank Working Paper Series_ , 3953.

- Suwa-Eisenmann, A., and T. Verdier (2007) Aid and Trade, _Laboratoire d’Economie Appliquee Working Paper_ , 0709.

- Walkenhorst, P. and T. Yasui, (2003), Quantitative assessment of the benefits of trade facilitation, TD/TC/WP(2003)31/FINAL, OECD.

- Wilson, J. S., Mann, C. L., and Otsuki, T. (2003). Trade facilitation and economic development: Measuring the impact. _World Bank Working Paper_ , 2988.

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20
- Lizano Fait, Eduardo (1992). _Estado y Economía en América Central_ . Paper prepared for the Congreso Internacional sobre Estado en América Latina: Orden Democrático, Cambio Sistemático y Perspectivas. Asociación Alemana de Investigación en América Latina. Mimeo.

- Mesalles, Luis (1998). “Condiciones Macroeconómicas de la Economía Costarricense”, in _Estabilidad y Desarrollo en Costa Rica. Las Reformas Pendientes_ . San José: Academia de Centroamérica.

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- ______(1992). _Welfare Effects of Trade Restrictions Removal: a Costa Rica Case Study_ . Master Thesis. The Ohio State University, Ohio.

- ______(1994). _The Political Economy of Trade Reform in Costa Rica_ . Doctoral dissertation. The Ohio State University, Ohio.

- Monge, Ricardo and Claudio González-Vega (1995). _Economía Política, Proteccionismo y Apertura en Costa Rica_ . San José, Costa Rica: Academia de Centroamérica and Centro Internacional para el Desarrollo Económico.

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42
communication. To this end, I use data on fixed telephone network penetration and construct a dummy variable equal to 1 for countries where the penetration rate at the baseline is below the median and 0 for those above the median. I then interact the dummy with the various measures of mobile phone penetration to explore the differential effect of mobile penetration across these groups. Table 6 presents interesting findings. First, similar to the results on the interaction with the income grouping, the effect of 2G network expansion on economic growth is statistically significant only in countries with low fixed telephone penetration at the baseline. This finding suggests that access to 2G mobile networks is a plausible substitute to fixed line telephony, hence the expansion in 2G networks enabled countries that hitherto had no/low access to telephone services to reap the economic gains associated with digital connectivity. The effects of 3G/4G connectivity are however present in countries with low as well as high fixed line telephone penetration. However, once again the effect in locations with low prior fixed line telephone penetration is relatively higher. Overall, the results indicate that access to mobile phones induces greater economic footprints in countries with previously low digital communication capacity.

# **5 Robustness Checks**

To assess the robustness of the results, I perform several robustness checks: First, by restricting the data to the period between 1998 and 2013, I show that the results hold for both the harmonized and non-harmonized nightlights data. Specifically, Table A4 shows the results from estimating the main IV equations using the restricted data on harmonized and non-harmonized nightlights data. In fact, the results in Table A4 show that estimates based on the harmonized nightlights data are slightly lower than using the non-harmonized lights data. This gives assurance that using the harmonized nightlights data does not lead to an overestimation of the impact of mobile phone coverage on economic activities.

Secondly, I conduct sensitivity analysis by investigating whether the baseline results are driven by a particular group of countries, i.e. if the results are sensitive to the country composition in the dataset. To this end, I re-estimate the baseline IV regression, while dropping one country at a time. Once again the results in Figure A2 in the online appendix show that the results are robust to country composition in the dataset.

Finally, I show in Figure A3 that the results are not driven by locational factors as sequential trimming of subnational districts away from the equator does not alter the main findings of the paper.

19
WPS3287

# **Explaining and Forecasting Inflation in Turkey***

## by

## Ilker Domaç

### Abstract

The growing adoption of an inflation targeting framework in emerging market economies has increased the importance of understanding inflation dynamics and forecasting its future path in these countries. This paper considers the case of Turkey and investigates the performance of models that have some theoretical foundations. To this end, the study focuses on mark up models, monetary models, and the Phillips curve. The findings suggest that the mark up models have the best in-sample performance followed by money gap models and the Phillips curve. The empirical results from out-of-sample forecasting performance for the period covering the new economic program (May 2001-December 2002), however, show that the Phillips curve and the money gap models perform better than mark-up models. These findings, in turn, imply that (i) Phillips curves augmented with the exchange rate and money models might provide complementary views in the Turkish context; and (ii) the relative importance of output gap and monetary disequilibrium in the inflation process has increased under the floating exchange rate regime. The results underscore the importance of relying on multiple models of inflation in the conduct of Turkish monetary policy.

### **JEL** **_classification_** : E31; E37; E58; C53

### World Bank Policy Research Working Paper 3287, April 2004

_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 names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available online at http://econ.worldbank.org._

> * I would like to thank Mark Griffiths and Tayyibe Gülek-Domaç for their helpful comments as well as Mustafa Eray Yücel for his valuable assistance.
Do Cash-Transfer Programs Protect from Poverty in the Case of Aggregate Shocks? A Study on Typhoon Yolanda in the Philippines. _∗_ Tobias Pfutze<sup>_†_</sup> World Bank _JEL Classification:_ D6, I3, O12 _Keywords:_ Cash Transfer Program, Aggregate Shock, Poverty, Philippines

> _∗_ The findings, interpretations, and conclusions expressed in this work are exclusively the author’s responsibility, and do not represent positions of the IBRD. The author is grateful to Yoonyoung Cho, Yasuhiro Kawasoe, and Jorge Avalos for help and comments.

> _†_ Level 3, Sasana Kijang, No.2 Jalan Dato’ Onn, 50480 Kuala Lumpur, Malaysia; Email: tpfutze@worldbank.org
annualized rate. Thus, returns match up exactly to the period covered by the contract, rather than just the year of the contract, as for the macroeconomic data. Payouts are not significantly correlated with Indian stock returns, however, perhaps reflecting that most Indian agricultural output is produced by small farms, rather than large traded firms.

# **6. Conclusions**

This paper has used historical rainfall data to estimate a putative history of payouts on Indian rainfall insurance policies. We have found that indemnities are concentrated in the extreme tail of adverse rainfall events. This insures households against severe shocks, but it also creates a highly skewed distribution of losses for an insurer writing rainfall insurance policies. This balance sheet exposure can be partially ameliorated by holding a portfolio of geographically segmented insurance contracts, or by using reinsurance markets.

We emphasize that much more research is needed to evaluate the promise of weather index insurance. For example, to shed further light on welfare benefits and to inform optimal contract design, theoretical and empirical work is needed to improve our understanding of the types of weather shocks against which rural household consumption is not well insured.

13
Table 2 Arab Unhemsity **Enrol** went, 1983-1984 or 1984-1985a

|_Country_|_Enrollment_|_Number_|_of_<br>_Universities_|
|---|---|---|---|
|Egypt|716,800||13|
|Syria|112,200||4|
|Morocco|87,200||_5_|
|Iraq|86,800||6|
|Lebanon|71,500||7|
|A'geria|71,200||8|
|Saudi Arabia|52,000||6|
|Jordan|33,400||7|
|Tunisia|29,600||1|
|Libya|18,300||3|
|Kuwait|17,000||1|
|United Arab Emirates|5,000||1|
|Qatar|4,700||1|
|Yemen Arab Republic|4,100||1|
|Oman|540||1|
|Total|1,310,340||65|

# a Includes external students.

Source: Derived from information in _Jnwrmaonal Handbook of Univesitie, 1986._ Table 3 Frequency Distbuton of' EnroOment In 6F Universities

|**_Enrolmneng_**<br>_Size_|_Number of Universities_|
|---|---|
|90,000 or nue|4|
|50,001 - 89,999|2|
|40,001 - 50,000|2|
|30,001 - 40,000|6|
|20,001- 30,000|3|
|10,001 - 20,000|15|
|5,001 - 10,000|12|
|3,001 -<br>_5,000_|7|
|1,001 -<br>3,000|10|
|1,000 or<br>lss|4|

Source: Derived from information in _Intenaional Handbook of Univers, 1986._ 4
_8_

**Table 1. Cash holdings and annual non-cash transactions per person**

||**_Cash_**<br>**_'_**<br>**_ra_**|<br>**_to M12_**<br>**_tio_**<br>|**_Cash_**<br>**_to G_**<br>_X_<br>|**_DPratio_**<br>|**_Valueof cas_**<br>**_perp_**<br>**_(U.S. 199_**|**_h holdings_**<br>**_erson_**<br>**_3 dollars)_**|**_Non-cas_**<br>**_t_**<br>**_per p_**|**_h_**<br>**_ransactions_**<br>**_erson_**|
|---|---|---|---|---|---|---|---|---|
|**_Country_**|**_1983_**<br>**_(1)_**|**_1993_**<br>**_(2)_**|<br>**_1983_**<br>**_(3)_**|**_1993_**<br>**_(4)_**|**_19833_**<br>**_(5)_**|**_1993_**<br>**_(6)_**|**_1983_**<br>**_(7)_**|**_1993_**<br>**_(8)_**|
|Switzerland|<br>.35|.34|9.90|7.86|3,524|2,676|na|67|
|Nethrlands|.33|.25|6.52|6.49|1,155|1,300|85|146|
|Belgium|.41|.30|9.12|5.95|1,411|1,187|35|101|
|Italy|.15|.16|6.37|5.75|610|1,191|13|29|
|Sweden|.10|.09|6.21|4.63|940|1,210|na|93|
|Norway|.33|.10|5.41|4.61|967|1,196|na|97|
|<br>Germany<br>4|.23|.20|3.53|3.89|742|995|86|139|
|France|.17|.15|5.08|3.58|810|759|88|157|
|Denmark|.12|.09|3.01|2.88|604|775|na|124|
|U.K.|.26|.08|3.72|2.84|410|520|74|115|
|Finland|.26|.07|2.07|1.97|277|438|83|120|
|Japan|.25|.27|7.59|8.43|1,795|2,387|19|39|
|Canada|.29|.20|3.16|3.43|529|716|88|128|
|U.S.<sup>4</sup>|.11|.11|1.79|2.06|328|509|184|292|

_Sources: IMF: International Financial Statistics, BIS: Payment Systems in the G-10 Countries (various issues)_ _1. Cash held by the public (equals currency and coin in circulation less that held by the banking system and the government)._ _2. M I equals demand deposits (transferable deposits) plus cash (defined above)._ _3. The 1983 figures are deflated using changes ineach country's CPI. 4. It is estimated that 35% of German currency and 60% of U.S. currency is held outside these countries, and the figures are adjusted accordingly (Boeschoten, 1992; Porter and Judson, 1995)._

**_Cash holdings and availability of POS andATM terminals._** The decreased reliance on cash for transactions is associated with the increased availability of credit and debit card terminals at the point of sale. This is seen in Figure 2(a) which illustrates the negative and statistically significant relationship between the availability of electronic funds transfer (EFT) POS terminals (terminals that accept credit - and debit cards) across 14 developed countries and the ratio of cash holdings to GDP for 1993 (R<sup>2</sup> .21). The increased availability of EFT-POS terminals leads directly to increased use, as evidenced from a very similar significantly negative relationship in Figure 2(b) between the annual number of EFT-POS transactions per person and the same cash/GDP ratio (R<sup>2</sup> - .25). Income and interest rates also affect the use of cash. The positive effect of national income is controlled for by our measurement strategy (cash/GDP) while the opportunity cost of holding cash is included. The correlation coefficient between the average of the monthly three-month money market rate (1987-1993) and the value of cash outstanding per person (1 993) is -0.64 for the countries shown in Table 1.
36 Appendix Table A3: Cotton subsidies and import tariffs in 2001, and average applied tariffs on textile and clothing imports in 2005<sup>a</sup>

||Cotton pr<br>subsi|oduction<br>dies:|Cotton<br>export<br>subsidies|Cotton<br>import<br>tariffs|Textile<br>import<br>tariffs|Clothing<br>import<br>tariffs|
|---|---|---|---|---|---|---|
||US$m|%|(%)|(%)|(%)|(%)|
|**High-income countries**|**3461**|**33.8**|**0.0**|**0.2**|**6.3**|**8.6**|
|Australia|27|2.2|0|0.0|11.6|22.0|
|United States|2969|40.2|0|0.6|7.3|9.4|
|Canada|2|7.1|0|0.0|5.8|14.0|
|EFTA|17|26.6|0|0.0|1.2|1.1|
|EU25|430|39.3|0|0.0|6.4|7.9|
|Japan|12|3.7|0|0.0|6.4|9.2|
|Korea & Taiwan|1|1.5|0|0.7|8.6|12.2|
|Hong Kong & Singapore|0|0.0|0|0.0|0.0|0.0|
|**Developing countries**|**450**|**1.5**|**0.4**|**2.6**|**11.2**|**18.4**|
|**_E. Europe &Central Asia_**|**_153_**|**_2.3_**|**_0_**|**_0.1_**|**_8.8_**|**_16.6_**|
|Russia|27|14.8|0|0.2|9.5|18.7|
|Turkey|115|3.9|0|0.0|13.3|19.9|
|Other E. Europe & CA|10|0.3|0|0.4|7.1|13.2|
|**_East Asia and Pacific_**|**_0_**|**_0.0_**|**_0.0_**|**_2.0_**|**_9.7_**|**_15.5_**|
|China|0|0.0|0|2.8|8.9|15.7|
|Indonesia|0|0.0|0|0.2|8.3|12.5|
|Malaysia|0|0.0|0|0.0|11.7|15.0|
|Philippines|0|0.0|0|1.1|6.0|12.8|
|Thailand|0|0.0|0|4.6|17.0|26.0|
|Viet Nam|0|0.0|0|0.0|30.4|39.1|
|Other SE Asia Pacific|0|0.0|0|2.4|3.4|3.1|
|**_South Asia_**|**_235_**|**_2.9_**|**_0.0_**|**_3.8_**|**_20.8_**|**_20.0_**|
|Bangladesh|0|0.0|0|0.9|29.5|36.6|
|<br>India|235|4.4|0|7.0|26.2|18.9|
|Pakistan|0|0.0|0|0.2|1.2|8.0|
|Sri Lanka|0|0.0|0|2.3|14.9|19.0|
|Other South Asia|0|0.0|0|0.0|8.2|8.7|
|**_Middle East & N. Africa_**|**_26_**|**_0.9_**|**_2.4_**|**_6.1_**|**_16.2_**|**_21.4_**|
|**_Sub-Saharan Africa_**|**_1_**|**_0.1_**|**_0_**|**_6.3_**|**_10.6_**|**_18.5_**|
|South Africa|0|0.0|0|10.3|19.2|31.4|
|Other SACU|0|0.0|0|0.4|12.7|7.4|
|Malawi|0|0.0|0|2.1|19.9|18.7|
|Mozambique|1|5.3|0|0.1|16.6|22.4|
|Zambia|0|0.0|0|3.0|7.7|28.9|
|Other Southern Africa|0|0.0|0|6.1|10.1|14.6|
|Nigeria|0|0.0|0|1.4|30.1|36.0|
|Uganda|0|0.0|0|0.6|22.6|28.9|
|<br>Other Sub-Saharan Africa|0|0.0|0|0.0|0.8|8.4|
|**_Latin America and Car._**|**_36_**|**_1.5_**|**_0.0_**|**_4.1_**|**_10.5_**|**_17.2_**|
|Argentina|2|0.6|0|1.4|16.2|15.4|
|Brazil|9|1.3|0|3.8|11.7|14.8|
|Mexico|25|4.5|0|0.8|5.2|10.5|
|Other Latin Amer & Car.|0|0.0|0|9.9|13.5|20.8|
50 RENT CONTROL IN KUMASI, GHANA consumption per month. Mean monthly consumption per capita is only C4,200 (US$47); the median is even lower at C3,300 (US$36).

# Household Size

There is a wide spread of household sizes in Kumasi around the mean of 4.5 persons. It is noticeable that there is a very gradual fade in frequencies above six persons, the largest household encountered had 52 persons. The extended family household is still common. Coresidential polygamy is evident in moslem dominated areas while polygamous Akans tend to separate their wives in different households, often in different houses.

<!-- Start of picture text --> Figure 3.7: Household Size, Selected Years Figure 3.8: Size Distribution by Sector<br>Percent of Each Year s Total Percent of Eacn Sector s Total<br>31. 20<br>Windigenous<br>25..jg oo Tenement<br>20 - .. ........ i nns E M<br>10- ... ... .... . ...... ~ ~ ~ ~ ~ ~ ~~~1<br>* ||ffiid....... 0 .<br>0-<br>Household Size I 2 3 4 5 6 7 6 9 i0 14 15-<br>Means 1970, 4 0. 1980, 4 8, 1986, 4 5 Means Indigenous 4 5, Tenement 4 2.<br>Sources Gnana (1978), Table 5, Tipple Government 5 7, Hign Cost 5 0,<br>(r817a), Table 18, 1986 Survey Total 4 5<br><!-- End of picture text -->

Households tend to be larger in the government sector than elsewhere. This is consistent with the 1980 data (Tipple, 1984a and 1987a) but the 1986 sectoral mean of 5.7 is considerably lower than the 1980 mean of 6.7 persons. Furthermore, whereas in 1980 the high cost sector had almost as large a mean size of 6.5 persons, this is reduced to 5.0 in the 1986 sample. In the 1980 data, this sector had a completely different distribution from all the other sectors with no single persons and only 1.6 percent two person households. The 1986 high cost sample is much closer to the other sectors. The change may be a result of sampling differences or it may reflect the way rents in the high cost sector have been kept low by the indirect effect of rent control. In an increasingly tight housing supply, the high cost sector appears to be losing its identity as the home of a select group and becoming integrated within the city as a whole.

There has been a very slight reduction in the mean household size in Kumasi between the 1980 and 1986 surveys, from 4.8 to 4.5.

It would, perhaps, be expected that "modernization," increasing urbanization, and an increase in availability of birth control might together have reduced the proportion of large households. In fact, the percentage of households with more than six persons has been holding fairly steady with 18 (1970), 21 (1980) and 19 (1986).
# **Electricity Provision and Tax Mobilization in Africa**<sup>_∗_</sup>

Moussa Blimpo,<sup>_†_</sup> Justice Tei Mensah,<sup>_‡_</sup> K. Ochieng’ Opalo<sup>_§_</sup> and Ruifan Shi<sup>_¶_</sup>

**JEL Codes:** O13,018,H2, H32, H32 **Keywords:** Electricity, Taxation, Reliability, Africa

> _∗_ This paper is part of a series of background papers to the “Regional Study on Electricity Access in Sub-Saharan Africa” produced by the Office of the Chief Economist of the Africa Region (AFRCE), World Bank under project code P156903. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations or those of the executive directors of the World Bank or the governments they represent

> _†_ The World Bank. Email:mblimpo@worldbank.org

> _‡_ Swedish University of Agric Sciences & World Bank. Email:justice.tei.mensah@slu.se; jmensah2@worldbank.org

> _§_ Georgetown University Email: Ken.Opalo@georgetown.edu

> _¶_ The World Bank.Email: rshi@worldbank.org
# <TABLE 9 HERE>

# **6 Conclusions**

While the increasing availability of micro-data has spurred a nascent literature on the impact of corruption on firm-performance, its impact on the efficacy of policy implementation itself has been largely neglected. Yet, whether corruption is associated with accelerated or delayed policy implementation is at the heart of the debate about whether corruption obstructs private sector development or instead enables it by allowing firms to mitigate the adverse effects of burdensome bureaucracy. Moreover, policy implementation times are a good metric for accessing public sector performance and delaying or accelerating policy implementation is one of the most direct channel(s) by which public officials can affect firm performance.

Using the World Bank’s Enterprise Surveys from 107 countries, this paper examines three testable predictions implied by the “grease the wheels” hypothesis. To start with, we test whether the duration of policy implementation is shorter for firms confronted with demands for bribes. The data reject this hypothesis. Instead, they exhibit a strong and statistically significant association between de facto policy implementation and demands for bribes; according to our preferred specifications firms confronted with demands for bribes take approximately 1.5 times as long to get a construction permit, operating license or operating license and 1.2 and 1.4 times longer to clear customs when exporting and importing ceteris paribus. These associations are robust to controlling for manager’s latent pessimism, and controlling for the subjective severity of corruption. The association between bribing and delays also obtains when pooling applications across different types of government services and controlling for firm-fixed effects as well as other firm’s corruption reports.

25