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37
extent that some customers were exclusively borrowing from those banks that experienced a deposit flight, at least temporarily, such borrowers may have found it particularly difficult to obtain new credit. In fact, at a time of heightened corporate risk and of tight liquidity, banks are very likely to turn down new credit applicants with whom they do not already have an established customer relationship.

<!-- Start of picture text --> Figure 9. Fixed Deposits at Commercial Bankss Figure 10. Fixed Deposits at Merchant Banksa<br>66- 8.0 ___________________________<br>64-75<br>7.0-<br>62-<br>6.5-<br>60-<br>6.0-<br>S~~~~~~~~~~~~~~~~~~~~~~~~~~~5 5<br>9 )01 9903 i9059i9:i0 i9909 ' i1 e1'4i01's40 959607 96109911 6 __<br>97.01 97!04' 97a07 97!10' 98101' 98104' '9807' 9ss!i<br>Figure 11. Fixed Deposits at Finance Companies 3 . Figure 12. Share Foreign Banks in Total Bank Deposits<br>36 23.5<br>P*~Od of<br>Rligh toF<br>23.0-<br>34-<br>22.5<br>22 22.0d<br>21.5-<br>30-<br>21.0<br>28 9 :~ 7 09:oss7 o' 99:0999:1911910 60 60 60 61 " ; - 20.51 17.01'97!03'97405'97!07'97!09'97 _ _ _ _ _ _ _ _ _ _ _ _ _ I 198!01 _ _ _ 98aO3'98!05'98!07'98!0, _ _ _ _ _ _ _ _ _ _ .T1 _<br><!-- End of picture text --> a: (% share in the total) Fifth, evolution of the yield curve, particularly beginning with September 1997 and throughout 1998 (see Box 3), suggests that economic agents expect short-term rates to increase (or they expect future monetary tightening) as demonstrated by the steep upward slope of the yield curve.

13
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30
opportunities it offers than for firms in industries that rely less intensively on the internet.<sup>5</sup> Guided by economic theory, we consider different measures for the internet intensity of industries drawing upon sources based on industry and firm-level data from the United States, China, and Vietnam.

A positive effect of internet penetration on firm export performance might be driven by other contemporaneous changes at the province level, such as investments in transport infrastructure. Therefore, our specifications control for province-year fixed effects which capture fixed and time-varying unobservable provincial attributes. Moreover, the specifications control for firm fixed effects to account for the unobserved heterogeneity across firms which could influence their export behavior. Hence, our econometric strategy estimates the within-firm variation in export performance over time due to increases in internet penetration in the firm’s province, which, we believe, helps us to identify the causal impact of the internet on firm performance in China. We address any remaining concerns about the endogeneity of internet penetration by using an instrumental variable strategy based on an indicator of telecommunications development in neighboring provinces.

We find that the rollout of the internet boosted manufacturing exports of firms in China. Specifically, growth in the number of internet users per capita in a province raises the probability that a firm participates in export markets, increases firms’ real exports and also their export-output ratios.

We take a closer look at the reasons for these findings. First, we examine which aspects of firm performance were affected and find that increased provincial internet penetration did not just enhance firm exports but also overall firm performance. Firms in China are not simply re-orienting their output to export markets but are increasing the scale of their production (measured by real output). The growth in firms’ real output is due to increases in both employment and labor productivity. The effects on firm total factor productivity (TFP) are somewhat less robust, suggesting that labor productivity growth is also driven by capital deepening. Second, we examine what types of firm communication were facilitated and find results consistent with improvements in communication with both buyers and input suppliers. Our estimates show larger effects in more communications-intensive industries that produce differentiated goods as well as in those that rely on a larger share of differentiated intermediate inputs. Third, we examine whether certain aspects of the new communication medium were particularly relevant. We find benefits from establishing

> 5 This identification strategy is inspired by Rajan and Zingales (1998).

3
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fiscal objective, but one that would necessitate the recovery of 11a costs incurred in the construction, expansion and maintenance of roads. Setting a price for road services equal to the variable maintenance costs and congestion costs may not be compatible with such a fiscal objective. The Bank has no guidelines specific to road transport which define the appropriate level of cost recovery from users. However, fiscal issues have been accorded much importance in identifying criteria that would justify a departure from efficiency pricing. Relatively little emphasis seems to be placed on equity issues in setting road user fees.

# B. THE PRACTICE

# B.1 Project SalRle

4. This review is based ov a sample of 22 projects. Our sample accounts for about 67 percent of the total number of road transport projects approved by the Bank during tY84 and FY85.

B.2 Discussion of Cost Recoverv Issues 5. Although efficiency prices are rarely explicitly calculated in the SARs, current pricing practices for road services in the sample countries are adequately discussed, including their efficiency and fiscal implications. Annual expenditures on roads and revenues collected through user charges are summarized below by country group:

|COMMTY|TOA<br>XC<br>AVZRAG<br>(inUSS m|DTRS<br>Z RAMSC<br>illion)|pINTERANE<br>AVZRAOC<br>-----(AsPare|maXPENITUZ<br>RANGE<br>ant<br>of TotalE|STOTALR<br>AVZRAG<br>xpenditur|EVENUE<br>RANTGE<br>e)-----|
|---|---|---|---|---|---|---|
|African|21.0|10-64|29.3|10-90|69.6|18-252|
|South& East<br>Asian|384.2|15-714|24.0|3-70|75.0|16-163|
|ZMZUA|161.1|35-354|31.0|25-42|141.6|101-163|
|Latin AmDricon|731.2|454-1,008|33.0|30-36|54.5|30-79|
|WholeSample|203.|-7<br>ral|AU||||
Navarro, 2019). Furthermore, the Victims and Land Restitution Law, which enables victims of the conflict to receive assistance and reparation, established preferential treatment for IDP women and reparations for survivors of sexual violence (Bouvier, 2016; Valcarcel & Samudio, 2017).

Notwithstanding, the legislative framework has not yet translated into conditions of gender equality. Gender discrimination prevents applicants from receiving property rights after their husbands have died or disappeared (Garcia-Godos & Wiig, 2014; Meertens, 2010). Access to justice also remains a challenge for victims of conflict-related sexual violence, despite an increase in the number of formal complaints (United Nations Security Council, 2020). One of the challenges to achieve gender equality in Colombia lies in deeply rooted gender norms. Women are expected to take on the bulk of domestic responsibilities, whereas men are seen as the head and main breadwinners for their families (Chant, 2002). Affordable, good-quality childcare services are lacking, and no legal provision exists for paid parental leave to be shared between both mother and father (World Bank, 2019, 2020). In fact, women do nearly four times as much as much unpaid domestic and care work as men do.<sup>1</sup> According to van der Gaag et al. (2019), alongside outliers such as Bangladesh and Algeria, Colombia is one of the countries where both the laws and gender norms around caregiving are relatively resistant to gender equality. These structural barriers are reflected in women’s lack of access to economic opportunities.

# **4. Theoretical Framework**

In general, norms specify rules, conventions and institutions that dictate what should or should not be done (Harper et al., 2020). Gender norms, in particular, are defined by Cislaghi and Heise (2020) as: Social norms<sup>2</sup> defining acceptable and appropriate actions for women and men in a given group or society. They are embedded in formal and informal institutions, nested in the mind, and produced and reproduced through social interaction. They play a role in shaping women and men’s (often

> 1 World Bank Gender Data Portal (national estimates). https://datatopics.worldbank.org/gender/. Accessed February 4, 2021.

> 2 Rule of behavior related to the differences in societal expectations for women and men. Individuals prefer to follow such rule if they believe that most people in their reference network conform to it and believe they should follow it (Bicchieri, 2005; Mackie et al., 2015).

7
# **Table A.26. The district fixed-effect RDD-DD regressions of individual-level outcomes with heteroscedasticity-consistent** **<u>standard errors</u>**

|||||Dependen|t variables||||
|---|---|---|---|---|---|---|---|---|
|Explanatory variables|Self-<br>employed<br>farm work<br>(yes=1,<br>no=0)|Self-<br>employed<br>non-farm<br>work<br>(yes=1,<br>no=0)|Having<br>wage job<br>(yes=1,<br>no=0)|Log of<br>monthly<br>wage (all<br>workers)|The annual<br>number of<br>healthcare<br>visits|The annual<br>number of<br>outpatient<br>healthcare<br>visits|Currently<br>attending<br>school<br>(children<br>aged 6-17)|Log of<br>education<br>subsidy for<br>students|
||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|
|Program * Post-program period|-0.1144***|0.0538***|0.0330***|0.5545***|0.3757***|0.3814***|-0.0080|1.2841***|
||(0.0141)|(0.0066)|(0.0104)|(0.0949)|(0.0600)|(0.0545)|(0.0179)|(0.0890)|
|(Poverty rate – 50) * Post-program|-0.0026|0.0046***|0.0026**|-0.0002|0.0561***|0.0523***|-0.0102***|0.0504***|
|<br>period|(0.0018)|(0.0009)|(0.0013)|(0.0118)|(0.0086)|(0.0079)|(0.0022)|(0.0103)|
|Program * (Poverty rate – 50) * Post-|0.0070***|-0.0056***|-0.0038***|-0.0338***|-0.0580***|-0.0547***|0.0075***|-0.0467***|
|program period|(0.0017)|(0.0008)|(0.0012)|(0.0111)|(0.0084)|(0.0077)|(0.0020)|(0.0094)|
|Age|<br>0.0243***|<br>0.0040***|<br>0.0104***|<br>0.1132***|<br>-0.0058**|<br>-0.0059**|<br>0.1571***|<br>0.3874***|
||(0.0006)|(0.0002)|(0.0004)|(0.0039)|(0.0027)|(0.0026)|(0.0070)|(0.0271)|
|Age squared|-0.0003***|-0.0000***|-0.0001***|-0.0015***|0.0003***|0.0002***|-0.0081***|-0.0197***|
||(0.0000)|(0.0000)|(0.0000)|(0.0000)|(0.0000)|(0.0000)|(0.0003)|(0.0012)|
|Male|-0.0653***|-0.0076***|0.0865***|0.9974***|-0.1495***|-0.1382***|0.0370***|0.1056***|
||(0.0044)|(0.0021)|(0.0030)|(0.0298)|(0.0182)|(0.0170)|(0.0057)|(0.0239)|
|Ethnic minorities (yes=1, Kinh=0)|0.1805***|-0.0990***|-0.0292***|-0.2248***|-0.2511***|-0.2432***|-0.1293***|0.7992***|
||(0.0082)|(0.0045)|(0.0061)|(0.0575)|(0.0426)|(0.0408)|(0.0098)|(0.0418)|
|District fixed effects|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Year fixed effects|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Constant|0.2242***|0.0402***|-0.0947***|-0.6763***|0.7249***|0.6527***|0.2662***|-1.1919***|
||(0.0140)|(0.0054)|(0.0088)|(0.0874)|(0.0418)|(0.0396)|(0.0394)|(0.1543)|
|Observations|128,446|128,446|128,446|128,446|86,980|86,980|50,645|50,645|
|R-squared|0.190|0.066|0.174|0.154|0.096|0.091|0.195|0.330|

Note: This table reports district fixed-effect RDD-DD regressions of individual-level outcomes. Robust standard errors in parentheses. Standard errors are clustered by district and village-year levels. *** p<0.01, ** p<0.05, * p<0.1.

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# F. SUMMARY OF FORECAST CASHFLOWS FOR SHIPBUILDING, TONNAGE DEMOLITION, VESSEL REPAIR AND CONVERSION (all indications are in billion US$, in constant 1992 prices)

|Year|| Shipbuilding<br>I<br>||Tonnage<br> <br>Demolition|Repair and |<br>Conversion|<br>_ANAUAL_<br>_TOTALS_|
|---|---|---|---|---|
|1993|36.000|1.040|6.536|_43.476_|
|1994|33.000|1.120|6.587|_40.707_|
|1995|35.000|1.200|6.801|_43.001_|
|1996|35.000|1.280|6.642|_42.922_|
|1997|37.000|1.360|6.483|_44.843_|
|1998|43.000|1.440|6.270|_50. 710_|
|1999|_55.000_|1.520|6.217|_62.737_|
|2000|56.000|1.520|6.164|_63.684_|
|**GRAND**<br>**TOTAL**|**_330.000_**|**10.480**|**51.700**|**392.100-**|