rafmacalaba/datause-encoder-data huggingface dataset:
The C&F market is very concentrated in Douala, with an aggregate market share of the 20 biggest agents that exceeds 55% for container imports destined to local consumption<sup>19</sup> . Despite the increase in the number of C&F agents in operation (+4% annually) the first players gain market share every year. This concentration has two adverse effects on dwell times: the first one is the low negotiating power of clients with these main C&F agents that leads to low level of service, the second is the development of low cost unprofessional C&F agents that have no choice but to compete on price at the expense of quality for the rest of the market. Table 8 below shows for example that the time efficiency of main C&F agents for successive operations before container exit from port is rather poor and in the lowest percentiles.

||**Relativeperformanc**<br>|**e(percentile)**<br>|||
|---|---|---|---|---|
|**Rank of**<br>**the C&F**|Time between<br>arrival and lodging|Time between<br>lodging and|Time between<br>liquidation and|Time between<br>payment and gate|
|**agent**||liquidation|payment|exit|
|**1**|**8**|87|58|95|
|**2**|50|58|60|76|
|**3**|**25**|74|**41**|78|
|**4**|51|**28**|64|**41**|
|**5**|59|**19**|61|52|
|**6**|**17**|**9**|83|90|
|**7**|50|54|75|50|
|**8**|62|**20**|82|23|
|**9**|**48**|56|94|61|
|**10**|74|50|81|**34**|

**Table 8 – Time performance of main Customs brokers** (Source: CAMEROONIAN CUSTOMS, 2009)<sup><u>20</u></sup>

#  **Low volume per operation** :

Efficient international trade logistics require standardization and predictability. However this standardization can hardly be reached when shippers operate with low number of containers per shipment and low volume of shipments per year. The average number of containers per Bill of Lading in the Port of Douala is 2.2 containers in 2009. Few shippers have regular shipments and the vast majority of flows is ordered by medium or small-sized companies that import less than 5 containers a year. The feedback from major C&F agents and port players is that these companies do not have enough regularity in their imports to have standard and robust processes in place. They have little control over import logistics and they often fail to consistently forecast delays in the logistics chain<sup>21</sup> . This is why they face much inefficiency in the clearance process including errors in customs

> 19 In contrast, this proportion is of 35% in the port of Dar Es Salaam.

> 20 Such data have been regularly monitored by Customs management since the introduction of performance indicators measurement. For more on this policy, see Cameroon customs 2010.

> 21 Source: local interviews, October 2010.

15
log expenditures is 10.90, resulting in a ratio of 0.0566.10 This implies that for a typical person in this sample, if the headcount poverty rate is 20 percent, the probability of at least one episode of apparent poverty in three years is 58 percent, while the probability that this person will be in poverty at least once in three years is 41 percent. To be "invulnerable" to poverty when facing such large variability in expenditures requires a level of log expenditures of at least 10.967 (which is called "Vulnerability to Poverty Line"), which is even higher than the mean (log) expenditures of 10.90. Because of this, 59 percent of the population is vulnerable to an apparent episode of poverty, almost three times of the currently poor." The level of vulnerability in 100 Village Survey sample is lower because the coefficient of variability is smaller. With a coefficient of variability 0.0345, the proportion of vulnerable population is 42 percent, about twice the poor.

This is interesting that the Mini-Susenas shows a _higher_ level of variability in expenditures, as this panel did _not_ span the worst of the crisis. One would have thought that the 100 villages data, by being conducted before and after the worst of the crisis would have much larger variability. There are a couple of possible explanations. First, we have done nothing about seasonality-because we can't. So perhaps the May to August comparison has less seasonal fluctuation than December '°This is a handy ratio, but it is not the "coefficient of variation" as this is the ratio of the standard deviation _offirst differences_ to the average of the _level._ We call this ratio the "coefficient of variability." " One way of thinking about this vulnerabili **t** y opoverty is a fornalization of the concept of "near poor," which is often used to illustrate the sensitivity of poverty rates to the poverty line. Vulnerability defnes "near poor" using a normalization based on the variability of changes in 15
|N|5412|4279|
|---|---|---|
|R-sq|0.260|0.295|
|F-test of instruments (p-value)|0.000|0.000|
|Hausman test (p-value)|1.000|1.000|
|Hansen J-test of overidentifying restrictions (p-value)|0.023|0.103|
|Country fixed effects|Y|Y|
|Time fixed effects|Y|Y|
|_Panel B_|(1)|(2)|
|Non-deposit funding|0.018***|0.015**|
||(0.006)|(0.007)|
|Assets|0.001***|0.001***|
||(0.000)|(0.000)|
|Equity|0.107***|0.109***|
||(0.004)|(0.005)|
|Assets growth|0.010***|0.010***|
||(0.002)|(0.002)|
|Overhead|-0.031***|-0.047***|
||(0.008)|(0.008)|
|Inflation|0.128***|0.117**|
||(0.034)|(0.051)|
|GDP growth|0.093***|0.066|
||(0.029)|(0.043)|
|GDP per capita|-0.002***|-0.002***|
||(0.001)|(0.001)|
|_First-stage_|||
|Instrumental variables|||
|Investment bank dummy|0.184***|0.179***|
||(0.008)|(0.009)|
|Non-bank credit institution dummy|0.273***|0.277***|
||(0.011)|(0.011)|
|Other dummy|0.032***|0.031***|
||(0.010)|(0.011)|
|N|5371|4241|
|R-sq|0.278|0.294|
|F-test of instruments (p-value)|0.000|0.000|
|Hausman test (p-value)|1.000|1.000|
|Hansen J -test of overidentifying restrictions (p-value)|0.000|0.000|
|Country fixed effects|Y|Y|
|Time fixed effects|Y|Y|

52
Table 9. Comparison of Selected Retail Food Prices in Armenia, Azerbaijan and Turkey, 1998 _(As percent of Turkey)_

|_Products_||_Azerbaijan_|_Armenia_|_Georgia_|
|---|---|---|---|---|
|Veal|KG|50%|42%|52%|
|Pork||n.a.|n.a.|n.a.|
|Margarine|KG|86%|78%|108%|
|Butter|KG|41%|37%|42%|
|Milk|L|72%|45%|71%|
|Eggs|Unit|125%|123%|112%|
|Bread, wheat|KG|80%|69%|67%|
|Crystal sugar|KG|82%|67%|73%|
|Potatoes|KG|169%|96%|141%|
|Average||88%|70%|83%|

_Sources: Statistical agencies of Armenia, Azerbaijan, Georgia, and Turkey._ Azerbaijani exports to Armenia could reach US$120 million, increasing total exports by US$100 million<sup>6</sup> , which equals ten percent of total exports.

# 3.2. Price Levels

Fully realizing that domestic price levels are determined by a multitude of factors, many of which fall outside foreign trade (including the exchange rates of local currencies, taxes, internal transport costs, wholesale trader markups, etc.), we still would like to compare and put into perspective the price levels in the three South Caucasus countries. Tables 8 and 9 present the comparative average prices of main commodity groups, including fuel and energy, agriculture and food, investment, and intermediate goods, among Armenia, Azerbaijan, Georgia, and Turkey. As these data refer to 1998, they do not take into account the different currency devaluation situations in the South Caucasus countries after the Russia crisis: Georgia has significantly devalued its currency after 1998, while Armenia and Azerbaijan have not. Therefore, the relative prices in Georgia today vis-a-vis Armnenia and Azerbaijan would be lower today than in 1998. Nevertheless, the above data might give some interesting insights.

As the data suggest, with respect to Azerbaijan, Armenian energy and agricultural prices are twice as high. Prices for fertilizers and timber are on par. The price of cement in Armenia is a third lower than it is in Azerbaijan and a fifth lower than in Turkey.

> **6** Export flows worth US$20 million could be rerouted to Armenia from more distant destinations.

26
41. The fourth feature of Brazilian debt that shaped the outcome when the shocks hit the economy, was the concentration of public debt holdings in mutual funds. The holders of public debt are mostly financial intermediaries, and among these, holdings are concentrated in a few agents (Table 2 ).<sup>11</sup> This concentration is undesirable because it amplifies rollover risk, as participating agents belong to the same sector and are affected by the same shocks. Additionally, financial intermediaries have a bargaining power derived from the potential for transmission of shocks to rest of the economy, which may lead them to assume greater risks and then demand special rescue operations in times of trouble.<sup>12</sup> One fact that explains why financial intermediaries hold public bonds is that the central bank allows computing government securities as reserve requirement holdings. In December 2001, 39 percent of total reserve requirements were held in the form of securities.

**Table 2**

**Holders of Domestic Public Debt**

|**Type of Agent**|**% of total**|
|---|---|
|Mutual funds|32.3|
|Brazilian Banks|30.4|
|Reserve Requirements|18.5|
|Corporates|7.0|
|Foreign banks in Brazil|4.7|
|Others|2.9|
|Households|1.0|
|Brokerage Houses|1.3|

Source: STN, August 2002, Relatorio do Mercado

# **B. POLICY REACTIONS TO THE CRISIS WITH NO DEGREES OF FREEDOM**

42. To mitigate the risk that the run on mutual funds’ deposits spread to the whole system, the central bank intervened buffering the contraction in market demand for public debt and facilitating its roll-over. To do so, the Central Bank increased its own holdings of public debt, and allowed a recomposition of private sector debt portfolios towards shorter maturity and away from fixed rate instruments. While the central bank held in its portfolio about 15 percent of total public bonds issued in 1999, that ratio increased to almost 30 percent by end 2002. This proportion is significantly higher in fixed rate instruments, where the central bank held over 60 percent of the total bonds issued in December.

> 11 Three banks and 7 mutual funds hold well over 50 percent of the government debt (Fratzscher and Del Valle, 2002).  Concentration is not peculiar to the Brazilian market.  Other more mature markets, such as the U.S. are concentrated, at least in operations with some types of instruments: the top quintile of primary dealers concentrates over 80 percent of total transactions in inflation-indexed securities (Sack and Elsasser, 2002).

> 12Two other reasons why the concentration of public debt holdings can be harmful:  a) it may give market power to the buyers that may collude to set prices.  b)  bond holding concentration could imply a regressive expenditure structure, given that interest payments on domestic debt constitute wealth redistribution from taxpayers to domestic bondholders if both group of agents are not the same.

19
views between June and August 2015. We collected information about the socio-demographic characteristics of study participants, their education, work history, finances and their expectations and attitudes. We also include a module to study social networks. We call all study participants through the duration of the study. In these interviews we administer a short questionnaire focused on job search and employment.<sup>13</sup> We have low attrition; in the endline survey, we find 93.5% of all job-seekers. We cannot reject the null hypothesis that there are no differences in attrition rates between treatment and control individuals when we study each treatment individually, or when we run a joint test for all treatments. A number of covariates predict attrition. Since none of these variables is correlated with treatment, we are not worried that this is affecting our results. Table A.8 in the Online Appendix presents the analysis of attrition. Attrition in the phone survey is also low; for example, we still contact 90% of respondents in the final month. Figure A.1 in the Online Appendix shows the trajectory of monthly attrition rates over the course of the phone survey.<sup>14</sup>

# **2.2 Surveys of firms**

We surveyed 498 large firms in Addis Ababa. We sampled these firms to be representative of the largest employers in the city, stratified by sector. We included all major sectors in the economy, including construction, manufacturing, banking and financial services, hotels and hospitality, and other professional services. To sample firms, we constructed a list of the largest 2,178 firms in Addis Ababa. Since no firm census exists for Ethiopia, we formed our own firm sample using a variety of data sources. In all, we gathered data from more than eight different sources; many came from government-maintained lists of formal firms, from each ministry for the respective sector covered by that ministry. For the manufacturing sector we used a representative sample of the largest firms from the Large and Medium Enterprise surveys, conducted by the Central Statistics Agency (CSA). Where firm size was available for the various sources, we imposed a minimum size cut-off off of 40 workers. In other cases we requested lists of the largest firms in each sector.

We drew the firms in our sample using sector-level weights that reflect the number of employers in that sector in the city. We constructed these weights using representative labour force

> 13 Franklin (2015) shows that high-frequency phone surveys of this type do not generate Hawthorne effects — for example, they do not affect job-seekers’ responses during the endline interview.

> 14 We do not report attrition rates at the very beginning of the phone survey since many respondents were only contacted for the first time in months 2 and 3 of the phone survey, either because they were surveyed towards the end of the baseline survey, and because of lags in setting up the phone survey.

7
- [4] Bagwell, K. and Staiger, R. (2012a). "The Economics of Trade Agreements in the Linear Cournot Delocation Model." Journal of International Economics, 88(1): 3246.

- [5] Bagwell, K. and Staiger, R. (2012b). "Pro...t Shifting and Trade Agreements in Imperfectly Competitive Markets." International Economic Review, 53(4): 1067-1104.

- [6] Bickerdike, C. (1907). "Review of A. C. Pigou’s Protective and Preferential Import Duties." Economic Journal, 17: 98–108.

- [7] Brander, J. (1995), "Strategic Trade Policy." in G. Grossman and K. Rogo¤ (eds.): Handbook of International Economics, Amsterdam: North-Holland, 3: 1395-1455.

- [8] Brander, J. and Spencer, B. (1985). "Export subsidies and international market share rivalry." Journal of International Economics, 18: 83-100.

- [9] Brückner, M. and Ciccone, A. (2011). "Rain and the Democratic Window of Opportunity." Econometrica, 79: 923-947.

- [10] Broda, C., Limão, N., and Weinstein, D. (2008). "Optimal Tari¤s and Market Power: The Evidence." American Economic Review, 98: 2032-2065.

- [11] Burgess, R. and Donaldson, D. (2011). "Can Openness Mitigate the E¤ects of Weather Fluctuations? Evidence from India’s Famine Era" American Economic Review, 100: 449-453.

- [12] Burgess, R., Dêschenes, O., Donaldson, D. and Greenstone, M. (2009). "Weather Related Death in India", MIT.

- [13] Deschênes, O. and Greenstone, M. (2007). "The Economic Impacts of Climate Change: Evidence from Agricultural Output and Random Fluctuations in Weather." American Economic Review, 97: 354-385.

- [14] Devarajan, S., Go, D.S., Li, G. (1999). "Quantifying the ...scal e¤ects of trade reform: A general equilibrium model estimated for 60 countries." The World Bank, Policy Research Working Paper 2162.

- [15] Dixit, A. (1984). "International Trade Policy for Oligopolistic Industries." Economic Journal, 94: 1–16

- [16] Dell, M., Jones, B., Olken, B. (2012). "Temperature Shocks and Economic Growth: Evidence from the Last Half Century." American Economic Journal: Macroeconomics, 4(3), 66-95.

22
1993 to positive and significant (r=0.09) in 2004. Thus it looks like the relationship for the minorities has become more like that for the majority.

We find rising landlessness among the poor in the fertile northern and southern deltas (Figure 6). Recall that the landlessness rate is much higher in the MD; 23% in 2004 versus 6% in the RRD (Table 2). The contrast is striking. In the RRD, landlessness rises with consumption while it is roughly the reverse in the MD.<sup>36</sup> The RRD is consistent with Case 2 in section 3 in which returns to schooling are relatively high, while the pattern for the MD is more consistent with Case 1, in which returns to schooling are relatively low; these differences in the labormarket returns to schooling accord with the evidence cited in section 2. The historical differences noted in section 2 also make it more likely that access to non-land inputs was more wealth-dependent in the MD, creating pressure toward a negative wealth gradient in landlessness. Over time we find rising landlessness among the poor in both regions, as predicted by our theoretical model. In the MD we also find a marked rise in landlessness among the highest consumption households, as well as for the bulk of the poor. Comparing Figures 6(a) and 6(b), it is evident that the big difference is in the incidence of landlessness among the poor. Among the poorest (log consumption around 7) the landlessness rate is about 5% in RRD versus 40% in MD.

Before exploring the sources of rising landlessness more closely, it is worth noting that there were also changes in the relationship between the size of land-holding and levels of living among those with land. Figure 7 plots (log) land holding (all types) against (log) consumption. We see that land holding conditional on consumption became more equal; the sharp positive

> 36 Recall that there will be a bias in using these regressions to infer the relationship with pre-reform consumption due to the fact that we are using post-reform consumption for 2004.  Unlike for Vietnam as a whole (Figure 3) when the true relationship is negative (as for MD) the sign of this bias is indeterminate.

24
7 2050. Selecting the specific year was essentially a matter of collective judgment, aided by a particular regression procedure.

The regression involved predicting judgTuents of the replacement year from last year's exercise. These predictors were included in a stepwise regression: 1980-85 female life expectancy; 1980-85 TFR; change in the crude birth rate from 1970 to 1980; family planning status; and a dummy variable for region, distinguishing East and Southeast Asia from other regions. Family planning status was coded as 3 for a strong family planning program (or contraceptive prevalence rate for the latest available date of 31 percent or higher); 2 for a moderate program (or contraceptive provalence of 16-30 percent); or 1 for a weak program (or contraceptive prevalence of 15 percent or lower). All variables contributed significantly, except change in the crude birth rate, which was dropped from the equation.

This equation and 'a similar but not identical equation estimated for previous exercises (Zachariah and Vu 1988) were used to predict the replacement year. Results were very close between the two equations. The predictions were examined and changed where warranted, in our judgment, and after comparison with U.N. Popunlation Division projected fertility trends (from the forthcoming 1988 re-ision).

For countries with fertility already below replacement level, the alternative assumptions applied were that fertility would remain at its current level up to 2000, and then gradually rise to replacement level by 2030.

For the replacement year, TFR is simply determined from the country's mortality level, and TFR for periods beyond that was kept at replacement. TFR for earlier periods was determined through a more complicated procedure. The entire period between 1985-90 and the replacement year was divided conceptually into three phases: an early, an intermediate, and a late phase. All countries were assumed to pass through the late phase, but some were assumed to skip the early phase, the intermediate phase, or both.

In the early phase, covering 1985-95, TFR remains constant or actually rises. Such a phase was defined for some suB-Saharan countries, particularly in the zone of high sterility in Central Africa. All other countries skip this phase.

In the intermediate phase, TFR declines at an accelerating pace, following a reverse geometric curve. This phase lasts up to 1995 or 2000 for many countries in Asia, Latin America, and North Africa. For all subSaharan African countries (whether or not they have an early phase), the intermediate phase lasts until halfway between 1995 and the replacement year.

In the late phase, the TFR decline decelerates, following a geometric curve, or TFR may actually rise (if fertility is below replacement), also following a geometric curve. This phase covers the
Month Follow-Up) using the control group’s mean and standard deviation.

4. _The Strengths and Difficulties Questionnaire (SDQ) (Goodman, 2001; Woerner et al., 2004)_ , a 25-item, parent-report questionnaire that screens for both behavioral problems and pro-social (positive) behaviors. The SDQ includes four problem-behavior subscales ( _Emotional Symptoms, Conduct Problems, Hyperactivity/Inattentiveness,_ and _Peer Relationship Problems_ ), along with a pro-social subscale. Examples of problematic behaviors include “Child is easily distracted, concentration wanders,” and “Child is often picked on or bullied.” Pro-social behavior items include “Child is kind to younger children,” and “Child shares readily with other children.” All items were translated, back translated, and approved by the test author.<sup>28</sup> The SDQ has been used in several African countries, including Kenya (Oburu, 2005) and South Africa (Cluver et al., 2007). For our administration, all items were read to the caregiver, who provided a response indicating her degree of agreement with the statement. Scores were determined for the four behavior problem subscales, which were aggregated into a total difficulties (problem) score, and the pro-social subscale separately. The total difficulties score and the pro-social scores were then standardized at each round (baseline, 18-, and 36-month follow-up) using the control group’s mean and standard deviation. Finally, the total difficulties index was multiplied by -1 so that a higher score indicates fewer difficulties.

5. _Kaufman Assessment Battery-Children, 2_<sup>_nd_</sup> _Edition (KABC-II) (Kaufman & Kaufman, 2004)_ , a suite of cognitive tests from which we adopted three tasks that performed well in piloting: _Hand Movements_ , _Number Recall_ , and _Triangles_ .<sup>29</sup> _Hand Movements_ is a non-verbal, short-term motor memory task requiring children to copy increasingly difficult hand movement sequences. For this test, the assessor demonstrated the movements by touching the table or floor as prescribed (e.g.

> 28 The Chichewa version of the SDQ can be found online here:

> <u>http://www.sdqinfo.com/py/sdqinfo/b3.py?language=Chichewa. The website also provides instructions</u> for scoring.

> 29 The Kaufman scales have been used in Kenya (Holding et al., 1999), Senegal (Boivin, 2002), and Uganda (Bangirana et al., 2009). The KABC-II test materials can be purchased through <u>http://www.pearsonclinical.com/psychology/products/100000088/kaufman-assessment-battery-forchildren-second-edition-kabc-ii.html.</u>

58