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37
i

# OPTIMAL USER CHARGES AND COST RECOVERY FOR ROADS IN DEVELOPING COUNTRIES

## TABLE OF CONTENTS

||||PA"|
|---|---|---|---|
|Execu|tiveS|wnmary..................|iv|
|I.|INT|RODUCTION.............................|1<br>I|
|II.|OPT|IMAL PRICING MODEL..|3|
|III.|ASS|UMPTONS UNDERLYITNG<br>OPTIMAL PRICING<br>|.<br>.<br>9<br>|
||3.1|Acceptable Simplifying Assumptions ..|_9_<br>|
||3.2|Unacceptable Simplifying Assumptions ..|11|
|IV.|REL|AX1NG UNACCEPTABLE<br>ASSUMPTIONS<br>AND||
||THE|CASE OF TUNISiA.....**.......**..............|....<br>15<br>|
||4.1|Relaxing Unacceptable Assumptions .<br>.........................|15<br>|
||4.2|The Case of Tunisia .........................|17|
|V.|FIN|ANCING REMAINING EXPENDITURES..............|...........<br>19|
|**vTr**||_C_<br>**_Ir_**<br>**_rt_**flEVCOWERY<br>........................|.<br>_2A_|
||6.1|Variable and Common Costs<br>............<br>...........|..<br>24|
||6.2|Recovering Collective Common Costs .........................|26<br>|
||6.3|Is it Feasible to Charge for Congestion? .........................|30|
|_VII._|APP|LYING THE PRICIYiGMODEL|**-22**|
|VIII.|**OTH**|**ER ISSES**AND CONCLUSIONS .37||
|Annex|1|Calculation of Congestion Costs for Tunisia .39||
|Annex|2|Recent Estimates of the Price Elasticity<br>||
|||ofD=m=_dfor Transpol-A<br>.........<br>.................|<br>. . . ....<br>43|
|Refere|nces|.......|47|
|Fig.|1.|Relationship Between Vehicle Operating Costs in||
|||Tunisia and the Roughness of the Road Pavement .|11|
ownership under individual interviews). We also find that the (positive) interaction effects between the business-as-usual survey approach and variables on marital status, age, and rural residence tend to be stronger for men (and in particular regarding exclusive as opposed to joint land ownership).

# **4.2 (Parcel-Level) Intra-household disrepancies in reporting, and discrepancy analysis**

To better understand the intra-household dynamics underlying the results above, we examine spouses’ reporting discrepancies on ownership and rights over the same agricultural parcel. Since overall agreement between spouses was very high (Table 3), regressions looking at overall discrepancies across ownership and rights do not reveal much information about driving factors (Appendix Table A5). Also, not all forms of disagreement have the same gender implications. For example, within the relatively more common areas of disagreement highlighted in Table 3 — where one spouse reports joint ownership, and the other reports not owning land — inferences about gender gaps in ownership/rights are very different depending on whether the wife is the one reporting joint ownership/husband reports not owning (wife attributes some landholding status to herself) — or whether the husband reports joint ownership, but she does not consider herself a land owner (wife attributes no landholding status to herself).

Table 6 presents results for these two more common discrepancy scenarios, across reported and economic ownership. Specifically, columns (1-2) (scenario 1) reflect the woman reporting less (no) reported or economic ownership for herself, respectively, as compared to columns (3-4) (scenario 2) where she reports joint land ownership, but the husband says he does not own land. Generally, the results show that greater household status for women is negatively associated with scenario 1, and positively with scenario 2 where they attribute some land ownership to themselves. Female household heads are significantly less likely to fall in scenario 1, for example. Scenario 1 is also positively associated with patrilineal marriages (for discrepancies in economic ownership, in particular). Women who are the main decision-makers over any plot in the household are also significantly less likely to fall in scenario 1, and more likely to fall in scenario 2 (although the significance is weaker). One potential reason — as discussed earlier, and in Jacobs and Kes (2015) — is that if interpretation around “joint” ownership is unclear, the husband in scenario 2 may interpret the wife as having exclusive ownership, whereas the wife still tends to attribute some ownership to him (perhaps due to cultural factors). This would also be consistent with the wife having a main decision-making role around agricultural activities in the household.

24
# **4.4 Additional influences on import protection: Retaliation capacity and WTO dispute jurisprudence**

Because trade policy is a repeated game played between sovereign states, the expected trading partner _reaction_ to a new import restriction is also likely to endogenously affect how countries implement import protection in the first place. Historical evidence from the Great Depression has long established expectations that retaliation can have important effects; e.g., Irwin (2011) argues that the trading partner retaliation to the U.S. Smoot-Hawley tariff in 1930 severely curtailed U.S. exports.

Research on more recently implemented policies shows how the latent threat of meaningful foreign trade retaliation is also likely to affect the channels through which import protection arises ex ante. Blonigen and Bown (2003) use the setting of industry applications for U.S. antidumping to illustrate how the presence of this tailor-made – i.e., product-specific and trading partner-specific – instrument presents opportunities for import protection to be funneled toward certain countries and/or industries that lack the capacity to retaliate. Similarly, Bown (2004) provides cross-country evidence to argue that the incentives inherent in the multilateral system’s formal dispute settlement procedures affected government choices of whether to implement protection through GATT-consistent instruments during 1973-1994.

Finally, the WTO’s dispute settlement system is also likely to influence the instruments of import protection that member governments apply through means other than its ability to authorize retaliation.<sup>14</sup> Sykes (2003), for example, identifies problems stemming from Panel and Appellate Body decisions resulting from legal challenges to national use of import restrictions under the WTO’s Agreement on Safeguards. Not only did these WTO rulings strike down virtually all challenged instances in which governments had applied this nontariff instrument, but the resulting jurisprudence failed to provide

> 14 Surveys of the empirical literature on GATT/WTO dispute settlement include Busch and Reinhardt (2002), Busch and Pelc (Forthcoming) and Bown (2009, chapter 4); the latter includes a discussion of the potential for GATT/WTO disputes to affect the endogenous formation of trade policy and thus choice of instruments of import protection.

19
Table 6: Productivity Decompositions and Policy Changes: Baseline Results

||Aggregate|Average|Reallocation|
|---|---|---|---|
||(1)|(2)|(3)|
|Final Goods Tariff|-.055|-.044|-.010|
||(.026)<sup>_∗∗_</sup>|(.030)|(.015)|
|Input Tariff|-.560|-.556|-.004|
||(.105)<sup>_∗∗∗_</sup>|(.115)<sup>_∗∗∗_</sup>|(.061)|
|FDI Reform|.023|.049|-.026|
||(.013)<sup>_∗_</sup>|(.014)<sup>_∗∗∗_</sup>|(.010)<sup>_∗∗∗_</sup>|
|Delicensed|-.007|.004|-.011|
||(.017)|(.017)|(.011)|
|Obs.|17074|17074|17074|
|_R_<sup>2</sup>|.086|.083|.014|

Each observation is a state-industry. Dependent variable names are given at the top of each column. “Aggregate” indicates market-share-weighted mean productivity, “Average” indicates unweighted mean productivity, and “Reallocation” indicates the covariance between market share and productivity. All specifications are fixed-effects analyses at the state-industry level, and include year dummies. Each observation is weighted by the total number of firms in the state-industry across all years, and standard errors are clustered at the state-industry level.

44
that experienced a banking crisis and increases in the Tier 1 capital ratio in its aftermath. The 2.8 percentage point increase in the Tier 1 capital ratio is both statistically significant and economically meaningful. When we examine changes using simple leverage (equity over total assets), we do not find a corresponding significant increase. These results are reported in column (3). In column (4) we examine whether countries that experienced a crisis have made changes to the definition of Tier 1 capital which could help explain the statistically insignificant relationship between banking crisis and increases in simple equity ratios. We find that countries that experienced a crisis have relaxed the definition of Tier 1 capital more than other countries as their Tier 1 stringency index declined by 0.68 points more than non-crisis countries. This decline corresponds to about 40 percent of a standard deviation of the Tier 1 stringency variable and is therefore economically significant.<sup>22</sup>

**Table 2: Changes in capital ratios and stringency**

|VARIABLES|(1)<br>ΔRegulatory<br>Capital/RWA|(2)<br>ΔTier1/RWA|(3)<br>ΔEquity/TA|(4)<br>ΔTier1<br>Stringency|
|---|---|---|---|---|
|Banking Crisis|2.136*|2.809***|1.176|-0.675**|
||(1.190)|(0.962)|(0.840)|(0.292)|
|ln(GDP per capita) 2010|-0.313|-0.139|-0.618*|-0.169|
||(0.679)|(0.489)|(0.354)|(0.200)|
|Inflation 2010|0.036|0.101|0.032|0.095*|
||(0.183)|(0.142)|(0.097)|(0.054)|
|ln(population) 2010|-0.872***|-0.777***|-0.518***|-0.019|
||(0.251)|(0.287)|(0.141)|(0.067)|
|Regulatory Quality 2010|0.896|1.351|-0.024|0.575**|
||(0.968)|(0.985)|(0.577)|(0.262)|
|Level of dependent variable 2010|-0.346|-0.409***|-0.371***|-0.823***|
||(0.210)|(0.130)|(0.100)|(0.099)|
|Constant|23.464**|19.771**|18.207***|6.299**|
||(9.258)|(7.838)|(4.059)|(2.543)|
|Observations|91|80|97|90|
|R-squared|0.226|0.389|0.279|0.515|

Note: *, **, and *** represent statistical significance at 10%, 5%, and 1% two-tailed level, respectively. Robust standard errors for heteroscedasticity appear in parentheses. Off-shore financial centers included in the computations.

> 22 The results are qualitatively similar if we include as crisis countries in the estimations those countries that experienced a banking crisis after year 2009 according Laeven and Valencia (2018), namely Cyprus (2011), Guinea-Bissau (2014), and Moldova (2014).

28
# **Table 6**

# **Income Effects of Full Preference Erosion**

||change in<br>|annual national in<br>$US million<br>|come,|
|---|---|---|---|
||Effects of|Effects of other||
||<br>EU MFN trade<br>liberalization|<br>OECD trade<br>liberalization|Total<br>preference loss|
|_African LDCs_|_-458.3_|_347.8_|_-110.5_|
|Botswana|0.2|16.3|16.4|
|Madagascar|-7.1|16.9|9.8|
|Malawi|-22.6|15.6|-7.0|
|Mozambique|-27.3|13.0|-14.3|
|Tanzania|4.6|-3.1|1.5|
|Uganda|-5.9|1.7|-4.3|
|Zambia|-18.9|-2.4|-21.3|
|Other Sub-Saharan Africa LDCs|-381.2|289.9|-91.3|
|_Asia/other LDCs_|_93.4_|_-180.9_|_-87.4_|
|Bangladesh|-101.0|-37.2|-138.2|
|Other Central/South Asia LDCs|194.4|-143.6|50.8|
|_Other Low-income_|_587.4_|_1463.1_|_2050.5_|
|India|174.0|101.8|275.8|
|Vietnam|413.4|1361.3|1774.8|
|TOTAL|222.5|1630.1|1852.6|

LDC and low-income classification is based on World Bank designations.

31
Figure 3: Change in sales/worker vs. ICT use <!-- Start of picture text --> Low competition with China High competition with China<br>−1.5 −1 −.5 0 .5 1 −1 0 1 2<br>Change in computers−per−worker Change in computers−per−worker<br>−1 −.5 0 .5 1 −1 −.5 0 .5 1<br>Change in the share of labor with internet Change in the share of labor with internet<br>−1 −.5 0 .5 1 −1 −.5 0 .5 1<br>Change in the share of labor with computer Change in the share of labor with computer<br>10 4<br>2<br>5<br>0<br>0<br>−2<br>−5 −4<br>Conditional ln(sales/worker) Conditional ln(sales/worker)<br>−6<br>−10<br>10 4<br>2<br>5<br>0<br>0<br>−2<br>−5 −4<br>Conditional ln(sales/worker) Conditional ln(sales/worker)<br>−6<br>−10<br>10 4<br>2<br>5<br>0<br>0<br>−2<br>−5 −4<br>Conditional ln(sales/worker) Conditional ln(sales/worker)<br>−6<br>−10<br><!-- End of picture text --> Source: Authors’ calculations with data from ENTIC 2009 and 2013, INEGI Note: For conditional ln(sales/worker) we use the residuals of a regression of ln(sales/worker) over size dummies, age dummies, ln(investment in fixed assets/worker) and the share of white-collar workers.

8
We also find that small firms’ full-time permanent employment is less sensitive to demand than large firms’. As we can see in Table 5, for a 1percent decline in a sector stock price, the decline in small firms’ employment in that sector, on average, is 2.7 percent smaller than that in large firms. In other words, large firms’ employment is more negatively correlated to demand sensitivity. One possible reason is that for small firms, firing workers is more costly. This is because the cost of finding and training good workers for small firms are probably higher, or perhaps the relationship between firms’ owners and workers are closer and more personal than in large firms, thus making the firing more difficult. We also interact the small firm dummy with the credit proxies but do not find differential impacts of credit needs on small firms.

# **5 Conclusion**

Drawing from The World Bank’s Financial Crisis Enterprise Survey, this paper presents evidence for the dramatic declines of demand for firms in six Eastern European countries and their impact on firms’ operation. An overwhelming majority of firms report the change in demand as the main effect and as the main cause for the improvement or further worsening of their businesses during the crisis. We find that changes in sales and capacity are significantly and negatively correlated with firms’ demand sensitivity, and not with various proxies for firms’ dependence on external finance before the crisis.

The results seem to suggest demand factors play a more important role in the firms’ performance during the crisis. Note that the results do not suggest that demand factors triggered the crisis—it might very well be the case that credit shocks did. Our conjecture is that as the crisis drags on, demand factors became more prominent. This has important policy implications. Since it is currently a demand problem, the focus should be on boosting investors’ and consumers’ confidence. Fiscal policies are the conventional instruments in this case.

17
- 23 -

act to restrain competitive forces by attempting to eliminate their existing rivals or preventing new ones from entering their market, and these actions too may be prohibited or regulated. Acts designed to eliminate competitors would include predatory pricing, 'unfair business practices" such as attempting to sabotage rivals' business operations or reputations, refusing to deal with customers who buy rivals' products, and other practices that go beyond the "normal" bounds or rivalry. There are some forms of behavior whose intent is ambiguous, for example, pricing a product aggressively in order to move down a learning curve (Spence, 1981, Ross, 1986); the latter clearly offers an opportunity for misapplied antitrust enforcement.

Incumbent firms may try to deter new entry through limit pricing strategies, threats of aggressive post-entry behavior, product differentiation strategies, attempts at vertical foreclosure, and other means. They can also use the political process to erect barriers to potential entry.

Interestingly, while modern theoretical contributions in industAial organization, particularly applications of game theory, have circumscribed the conditions under which economists believe firms can effectively deter entry C through their own actions<sup>24</sup> , political economic research, including the rent24 The literature on strategic entry deterrence has grown increasingly sophisticated over time, largely due to the contributions of modern game theory (Tirole, 1988, Chapter 8; Scherer and Ross, 1990, Chapter 10, and cites therein). This has made our analyses of firm behavior richer, but also much more complicated and qualified; static limit pricing, which once seemed quite straightforward in intent and effect (Modigliani, 1958) is a good case in point. The static limit pricing model assumes that an incumbent firm threatens to maintain the limit-price output even if entry occurs, thus making entry unprofitable and effectively discouraging it. However, absent some "commitment" to rivalry, if entry actually occurs, it will be more profitable to accommodate it than to carry out the threat. Such a threat is therefore not sub-game perfect and is not credible. As a result, it would not deter entry.
16 resources of the DGA. The more bank failure resolution approaches this polar alternative, the greater would be the need for backstop financing for the DGA.<sup>16</sup>

# **3.4. The "least cost" criterion and its implications**

Between the two extremes mentioned above, there are a continuum of alternatives where the contribution of the DGA to the "good" bank is controlled through some form of least cost criterion. For the purposes of this paper, the standard definition of this criterion implies that a good bank/bad bank type resolution should be implemented only if it imposes a cost to the DGA that is no greater that the cost that the DGA would incur if it were to pay out guaranteed deposits in cash, in exchange for a fairly privileged claim on the liquidation. **Four variables affect the potential size of the DGA contribution to the "good" bank under a least cost criterion:** (i) the size of the insolvency "hole" of the failing bank _-ceteris paribus,_ the greater the insolvency the greater the potential contribution by the DGA; (ii) the priority of claim accorded the DGA in the liquidation - the higher such priority, the smaller the potential contribution by the DGA; (iii) the share of guaranteed deposits in the liabilities of the failing bank -the higher such share, the higher the potential contribution by the DGA; and (iv) the degree of loss in the value of assets as they move into judicial liquidation -the greater the loss, the larger the potential contribution by the DGA. Rather than examining in detail the effects of the various combinations of these four variables on the contribution by the DGA to the "good" bank, it appears preferable to lay out two sets of general observations that are helpful in clarifying the policy options.

First, only benefits can be obtained from **improving and enforcing prompt corrective action and early intervention rules,** as these would reduce the probability that insolvent banks continue to operate and minimize the size of the insolvency "hole" of a bank subject to Art. 35 bis. As a consequence, the soundness of the banking system would be better protected and the DGA's resources would be less exposed to losses. Similarly, major benefits could also be obtained from **streamlining the liquidation process,** as this would imply a lesser loss of value for assets under liquidation and, thus, a lower risk of loss for the DGA under a least cost criterion. Regardless of whether the 16 Under Argentine-type convertibility, backstop financing to a DGA could not entail money creation by the Central Bank; it would have to come from domestic or, preferably, external debt.