rafmacalaba/datause-encoder-data huggingface dataset:
declarations, delays in transmission of import documents by suppliers or shortage of liquidity, and this inefficiency is in general synonymous of long delays and high import costs.

The impact of unpredictability over logistics costs has been estimated to 25 or 30% of factory price (Arvis _et al._ , 2010) while the impact on delays is in days.<sup>22</sup>

##  **Concentration of shipping flows**

Another significant pattern for containers imports to the port of Douala is the concentration of shipping flows along a few main shipping routes. The top 3 shipping routes account for example for 70% of total imports. This creates disruption in the pattern of arrivals and punctual congestion at the later clearance steps (transfer to the yard, customs clearance formalities, etc.) that generate serial delay in the whole chain of operations. This is also a main driver of discretionary clearance behaviors as will be shown later.

|**Port of origin**|**Proportion of container imports**|**Cumulative proportion**|
|---|---|---|
|**Algéciras**|34%|34%|
|**Las Palmas**|22%|56%|
|**Antwerp**|14%|70%|
|**Singapore**|11%|81%|
|**Dubai**|3%|84%|
|**Genoa**|3%|87%|

**Table 9 – Concentration of container imports along main shipping routes (** Source: CAMEROONIAN CUSTOMS, 2009)

3. BEYOND FIGURES: STRUCTURAL GROUNDS OR ADVERSE BEHAVIORS?

# **Structural inefficiencies**

_Operational inefficiencies_ <!-- Start of picture text --> Vessel Vessel Transfer<br>arrival berthing & to the Delivery Exit from<br>Operational dwell time buoyat dischargecontainer yard or ODCY truckonto 1 to 8hyard<br><2h<br>24 to 48h <1h<br><!-- End of picture text -->

**Figure 2 – Sequence of operations in the Port of Douala and typical times** (Source: DIT)

The operational inefficiencies of port operators are often identified as major hindrances to the achievement of the “7 days” dwell time objective set in 1997 for the Port of Douala community.

> 22 Further research is probably needed to estimate the impact of regularity on dwell time and Customs clearance efficiency.

16
# **4 Private and regulated duopoly**

We next explore the optimal industrial organization when the fixed cost _K_ becomes smaller or equivalently, when the value of operating the firm after investment, _V_ , becomes larger.<sup>22</sup> This is relevant because in the last two decades some industries such as telecommunication have experienced dramatic technological and/or demand changes resulting both in a decrease in fixed costs and an increase in demand. Moreover, for a given industry the demand is generally weaker in developing countries than in industrialized countries, resulting in lower _V_ . That is, for the same population size, the number of consumers and their propensity to pay are higher in rich countries. This difference might again imply different industrial policy. We first study the case of a private duopoly.

## **4.1 Private duopoly**

To simplify the exposition, we rule out franchising in the sequel. The results are nevertheless robust to more favorable specifications of the franchise fee.<sup>23</sup>

### **A4**

Private duopoly ( _PD_ here after) is modeled as Cournot duopoly with asymmetric information between firms. Each firm gets private information on its own marginal cost but it is not informed about the competitor’s marginal cost. As in any Cournot game, each firm maximizes its profit taking the other firm’s output as given. The timing of the game is as follows: First both firms simultaneously make the investments _K_ . Second, each firm _i ∈{_ 1 _,_ 2 _}_ learns the realization of its own marginal cost _βi_ and chooses its

> 22From figure 1, we see that a private monopoly is less likely to be preferred to a regulated monopoly as _K/V_ diminishes. However this result is incomplete. For lower _K/V_ more than one firm may enter the market.

> 23Considering _F >_ 0 would reinforce the bias in favor of the private monopoly in Lemma 6 because franchise fees are higher with a private monopoly than with a private duopoly. Empirically Wallsten (2000) finds using panel data of 17 developing countries that exclusivity periods (i.e., temporary monopoly position) can double the firm’s sale price (i.e., _F_ ) in telecommunication industry.

21
24 in government authority. For example, Friedman, et al. (2000) show empirically that countries with more corruption have a higher proportion of activities in the unofficial economy. The private sector depends on effective legal regulation. Torgler and Schneider (2007, 2009) show that that improving governance and institutional quality and tax morale helps lessen a possible incentive to go underground. The results are quite robust when using more than 25 proxies of governance and institutional quality, testing for endogeneity and running a broad variety of specifications. Hanousek and Palda (2004) work with survey data from the Czech and Slovak Republics, Hungary, and Poland, and find strong support for the hypothesis that there is a positive correlation between tax evasion and the perceived government services based on the taxes paid. A government based on a well-functioning democracy produces more trust than a dictatorship. A lack of public trust undermines state revenues and thus the government‟s ability to perform its function. Trust in public officials might tend to increase taxpayers‟ positive attitudes and commitment to the tax system and tax-payment, which finally exerts a positive influence upon tax compliance. Institutions that taxpayers perceive as fair and efficient might have a positive effect on tax morale, conditional on whether society views taxes as a price paid for government‟s positive actions. Thus, if taxpayers trust their public officials, they are more willing to be honest. If the government acts trustworthily, taxpayers might be more willing to comply with the taxes. Similar to the tax administration, the relationship between taxpayers and government can be seen as a relational contract or psychological contract, which involves strong emotional ties and loyalties. Such a psychological tax contract can be maintained by positive actions, based on trust. If the government tries to generate trust with well-functioning institutions, co-operation can be initiated or increased. Furthermore, when taxpayers are satisfied with the way they are treated, the co-operation is enhanced. If the outcome received from the government is judged to be fair in relation to the taxes paid, no distress arises. The studies of 1990s show that trust in the state influences tax morale.
Table 6 presents the results for different specifications of Equation 2 on a sample of 10,728 children in rural areas. As mentioned in the previous section, we focus on _completed_ rainy seasons since a child was born. For instance, _ΔR1_ is the deviation of rainfall during the first completed growing season experienced by a child, and _ΔR2 and ΔR3_ are the second and third seasons, respectively. In the first four columns we include the deviation from normal rainfall, each with a different set of controls.<sup>25</sup> In general, the estimated regressions show that rainfall shocks at early life have a significant effect on the HAZ scores. Moreover, the positive coefficients suggest that the benefits to child health through the income channel more than compensate any negative impact that higher rainfall may have on child health due to the expansion of water-borne and other diseases.

As opposed to the weight-for-height case we are now able to control for the corresponding temperature shocks.<sup>26</sup> Note that while rainfall shocks have an ambiguous effect on child health (depending on the relative strength of the income and disease environment channels), temperature shocks always have a negative impact on child health, especially in certain temperate locations. Higher temperatures increase the incidence of diseases and also reduce agricultural yields, lowering the subsequent nutritional intakes. We present the results in column (5). In line with our reasoning we find that temperature shocks at early life have a negative impact on height-for-age Z-scores. In addition, the coefficients on rainfall deviations are still negative and significant, and the inclusion of temperature shocks has not affected their magnitudes.

Lastly, we test for nonlinearities by including the square of weather shocks. As we already mentioned, if rainfall shocks affect child health linearly, then any increase in the variance of rainfall (for example, induced by climate change) might not have any additional impact on the expected health outcome. In contrast, if a quadratic relationship exists between shocks and health then, any change in its variance will also affect the mean health outcome. Results presented in column (6) show that all the square coefficients are not statistically significant implying that rainfall affects health linearly. Further, their inclusion does not change the significance and magnitude of either the rainfall or the temperature shocks.

So far we have shown that past weather shocks impact child health, but we have not been able to say anything about whether these shocks have a permanent effect or not. In other words, saying that

> 25 Controls include fixed effects by age, month of birth, month*year of interview, season*year of interview, and state.

> 26 Unfortunately, the quality of the temperature records for 2008, the year of the last and larger DHS survey, are not reliable enough, and hence we decided to exclude temperature in the weight-for-height regressions. In the case of height-for-age, the last completed growing season for the vast majority of the sample is 2007.

25
We end with some caveats. First, due to space limitations, our review has focused on welfare impacts and we have neglected issues of insurance, coping mechanisms, and social protection policies. Second, the review centered the discussion on one-shot price shocks. In particular, we have not covered the literature on the effects of commodity price volatility. In addition, even in the case of one-shot price shocks, we should note that there might be hysteresis in the effects. In other words, a price shock may have long term implications, even if the price change reverts at a later date (Baird, Friedman and Schady, 2011). These themes require careful consideration in future assessments of the developmental implications of price signals.

# **References**

Baird S., J. Friedman and N. Schady (2011). “Aggregate Income Shocks and Infant Mortality in the Developing World,” Review of Economics and Statistics, 93 (3), pp. 847–856.

Barnum, H. and L. Squire (1979). “A model of an Agricultural Household. Theory and Evidence,” World Bank Ocassional Papers No 27.

Barrett, C. and P. A. Dorosh (1996). “Farmers’ Welfare and Changing Food Prices: Non- Parametric Evidence from Rice in Madagascar,” _American Journal of Agricultural Economics_ , vol. 78, pp. 656–69.

Baulch, B. (1997). “Transfer Costs, Spatial Arbitrage, and Testing for Food Market Integration.” _American Journal of Agricultural Economics_ , 79(2): 477–487.

Benjamin, D. (1992). “Household Composition, Labor Markets, and Labor Demand: Testing for Separation in Agricultural Household Models,” _Econometrica_ , vol. 60, No.2, pp. 287–322.

Benjamin, D. and A. Deaton (1993). “Household Welfare and the Pricing of Cocoa and Coffee in Cte d’Ivoire: Lessons from the Living Standards Surveys,” _The World Bank Economic Review_ , 7, pp. 293–318.

27
Policy Research Working Paper 7746

# **Abstract**

Estimation of empirical relationships is prone to bias. Economists have carefully studied sources of bias in structural and quasi-experimental approaches, but the randomized control trial (RCT) has only begun to receive such scrutiny. This paper argues that several lessons from medicine, derived from analysis of thousands of RCTs establishing a clear link between certain practices and biased estimates, can be used to reduce the risk of bias in economics RCTs. It identifies the subset of these lessons applicable to economics and uses them to assess risk of bias in estimates from economics RCTs published between 2001 and 2011. In comparison to medical studies, most economics studies examined do not report important details on study design necessary to assess risk of bias. Many report practices that suggest risk of bias, though this does not necessarily mean bias resulted. The paper concludes with suggestions on how to remedy these issues.

This paper is a product of the Operations and Strategy Team, Development Economics Vice Presidency. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at eble@tc.columbia.edu.

_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 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._ Produced by the Research Support Team
|No. of workers (logs)*Herfindahl-||||||-6.125***|-6.144***|
|---|---|---|---|---|---|---|---|
|Hirschman Index||||||(1.981)|(1.978)|
|No. of Workers (logs)*GDP per<br>||||||-0.549*<br>|-0.371<br>|
|capita (logs)||||||(0.320)|(0.319)|
|No. of Workers (logs)*Starting a||||||-0.001|0.004|
|Business (DTF)||||||(0.016)|(0.016)|
|No. of Workers (logs)*Courts||||||0.014|0.028|
|Obstacle (cell average)||||||(0.363)|(0.359)|
|No. of Workers (logs)*Women<br>||||||0.376<br>|0.687<br>|
|can work the same night hours as||||||(0.696)|(0.704)|
|men Y:1 N:0||||||||
|No. of Workers (logs)*Women<br>||||||-0.233<br>|-0.119<br>|
|can work in the same industries as||||||(0.564)|(0.555)|
|men**Y:1 N:0**||||||||
|Exports (%, cell average)*WBL|||||||0.043|
|Index|||||||(0.363)|
|No. of Workers (logs)*WBL|||||||-3.295*|
|Index|||||||(1.880)|
|No. of Workers (logs)|0.518**|0.665***|0.716**|0.861***|0.869***|6.010**|6.143**|
||(0.245)|(0.258)|(0.282)|(0.289)|(0.288)|(2.527)|(2.532)|
|GDP per capita (logs)|19.350***|19.859***|21.294***|16.245***|6.741|8.508|7.740|
||(5.010)|(5.226)|(5.237)|(5.461)|(5.343)|(5.484)|(5.494)|
|Herfindahl-Hirschman Index||-6.955*|-6.569*|-9.727***|-6.613**|12.845*|13.158*|
|||(3.557)|(3.446)|(3.747)|(3.327)|(7.587)|(7.568)|
|Age of Firm (logs)||-0.470|-0.900***|-0.712**|-0.844**|-0.835**|-0.815**|
|||(0.362)|(0.342)|(0.357)|(0.355)|(0.354)|(0.354)|
|Foreign Ownership (proportion)||-0.791|-0.002|0.019|0.085|0.081|0.169|

87
WPS3784 coffee farmers typically have a high propensity to spend on other products produced in the rural communities. Increasing returns to commercial farmers could have substantial multiplier effects within rural communities. The challenge is to provide an infrastructure and framework by which rural markets can develop and flourish. Given the current level of development in Rwanda it is clear that this will require a significant response and engagement from the international institutions and donors.

# **References**

Balat, J. and G. Porto (2005) ‘Globalisation and Complementary Policies: Poverty Impacts in Rural Zambia’, NBER Working Paper 11175.

Besley, T. and A. Case (1994). “Diffusion as a Learning Process: Evidence From HYV Cotton,” mimeo, Princeton University.

Cadot, O., L. Dutoit and M. Olarreaga (2005) ‘Subsistence Farming, Adjustment Costs and Agricultural Prices: Evidence from Madagascar’, mimeo, World Bank.

Conley, T. and C. Udry (2004). “Learning About a New Technology: Pineapple in Ghana,” mimeo, Yale University.

Dabalen A., S. Paternostro and G. Pierre (2004). “The Returns to Participation in the Nonfarm Sector in Rural Rwanda” World Bank Policy Research Working Paper 3462.

Deaton A. (1989). Rice prices and Income Distribution in Thailand: A non parametric Analysis”. _Economic Journal_ 99 (395) (supplement), 1-37.

Deaton, A. (1997). _The Analysis of Household Surveys. A Microeconometric Approach to Development Policy_ , The World Bank and The Johns Hopkins University Press.

Delgado, C. J. Hopkins, and V. Kelly (1998). _Agricultural Growth Linkages in SubSaharan Africa._ Research report 107, IFPRI.

Foster, A. and M. Rosenzweig (1995). “Learning by Doing and Learning from Others: Human Capital and Technical Change in Agriculture,” _Journal of Political Economy_ , 103, 1176-1209.

Haggblade S, J. Hammer and P. Hazell (1991). “Modelling Agricultural Growth Multipliers”, _American Journal of Agricultural Economics_ , 361-378.

Heckman, J., H. Ichimura, and P.E. Todd (1997) "Matching as an Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Program." _Review of Economic Studies_ , 64, 605-654.

18
limited material is a 1990 analysis of MBA programs in Indonesia, and an analysis of MBA programs in South Africa.<sup>5</sup> More direct evidence of how employers view MBA graduates is limited. One source of information is an informal survey of senior finance executives by _CFO_ magazine, conducted in 1997.<sup>6</sup> The results of the survey are illuminating, but limited in scope: The survey found that 60% of the sample said that new MBA graduates learn too much finance theory and not enough about practical financial management. Also, 70% of the executives in the survey awarded a “C” or “D” grade to MBA graduates’ personal communication skills (out of a scale of A, B, C, D, and F with A being the best and F being the worst). In 1994, James Neelankavil conducted a more formal survey of human resource directors of Fortune 1000 firms about the quality of MBA graduates.<sup>7</sup> The results of this survey will be discussed in the following sections, and will provide the only source of comparison for this survey’s results.

Thus the research and analysis on the quality of MBA training has been quite limited, and the little that exists has looked at MBA training on a more modest scale than this survey has done (in terms of the number of firms surveyed and countries analyzed). In this sense, this work can be viewed as the first cross-country analysis of the quality of MBA graduates.

> 5Pesulima, L.S., “Empirical Investigation of the MBA Program in Indonesia: Academic versus Practitioner Perceptions,”  Nova University, Fort Lauderdale, Florida.  Published PhD thesis;  and Louw, L.,  “The Status and Nature of MBA Programmes in South Africa,”  University of Port Elizabeth. Port Elizabeth: Unpublished D. Com thesis.

> 6Harris, R. and Barr, S.,  “Incomplete Education _CFO_ Magazine, April 1, 1997.

> 7 Neelankavil, J., “Corporate America’s Quest for an Ideal MBA _Journal of Management Development_ , 1994, Vol. 13, No. 5, page 38-52.

5
household size reflects problems with the 1995 sampling design or administration of the questions regarding household membership.

**Table 19 Mean Household Size by Region**

|||_Hous_|_ehold size_||
|---|---|---|---|---|
|_Region_|_1985_|_1988_|_1993_|_1995_|
|Abidjan|6.18|5.88|5.98|5.82|
|Other Cities|6.41|6.33|6.19|5.27|
|East Forest|6.60|6.46|6.14|5.86|
|West Forest|6.03|5.60|5.68|4.63|
|Savannah|7.24|6.35|5.47|5.57|
|C6te d'Ivoire|6.51|6.16|5.91|5.46|

Source: 1985 and 1988: Demery and Grootaert (1993); 1993 and 1995: Priority Surveys.

**Table 20 Mean Size of Farm Households**

|||_House_<br>|_hold size_<br>||
|---|---|---|---|---|
|_Region_|_1985_|_1988_|_1993_|_1995_|
|East Forest|||||
|Export crop farmer|||7.38|6.23|
|Food crop farmer|||5.51|6.09|
|West Forest|||||
|Export crop farmer|||6.34|5.30|
|Food crop farmer|||4.77|4.15|
|Savannah|||||
|Export crop farm|||6.06|5.75|
|Food crop farmer|||5.50|6.10|
|C6te d'Ivoire|||||
|Export crop farm|6.92|6.70|6.70|5.86|
|Food crop farmer|7.06|6.38|5.47|5.66|

Source: 1985 and 1988: Demery and Grootaert (1993); 1993 and 1995: Priority Surveys.

**Table 21 Mean Size of Cocoa- Growing Export Farmer Households**

||_House_|_hold size_|
|---|---|---|
|_Region_|_1993_|_1995_|
|East Forest|7.49|6.10|
|West Forest|6.65|5.38|
|Savannah|7.16|6.25|
|C6te d'Ivoire|7.09|5.92|

23
<!-- Start of picture text --> ® 3month-lockdown 4 5 month-lockdown<br>20<br>ry<br>a<br>—== 15 4<br>2<br>e J<br>c<br>‘a 10 e<br>2 a * bd<br>ge<br>e¢<br>0<br>7 8 9<br>log(GDP per capita)<br><!-- End of picture text --> <!-- Start of picture text --> W Loss-making firms 4 Profit-making firms<br>0.3<br>v<br>A~<br>oe3 v Y YVowy<br>E 02 v<br>= ay<br>3<br>2<br>8 a 4 ‘<br>ao1 & A A Rk<br>A<br>0.0<br>7 8 9<br>log(GDP per capita)<br><!-- End of picture text --> <!-- Start of picture text -->
* 3 month-lockdown 4 5 month-lockdown<br>a<br>300<br>°<br>=<br>% a ry<br>‘»oO 200<br>E .<br>E<br>£<br>s 4 t<br>2 100 C4 k ae<br>a ° e ry<br>e<br>*<br>0<br>T 8 9<br>log(GDP per capita)<br><!-- End of picture text -->
# 1 Introduction

In this paper, we ask: What drives misreporting in agricultural surveys? We exploit objective and subjective measures of agricultural knowledge and adoption to study the determinants of misreporting, with a focus on the gender of the respondent. Findings from regression and costeectiveness analyses are used to formulate recommendations for extending our applications to standard rural household surveys.

Encouraging the adoption of improved technologies stands front and center of the agricultural policy agenda. The role of women in achieving food security is under investigation and more interventions look to specically aect women's agricultural outcomes (O'Sullivan et al., 2014). The number of ongoing rigorous impact evaluations on agricultural interventions is booming, aimed to test what works and how to inform policy decisions. Yet, determining what works is largely at the discretion of the methodology and indicators applied to measure eectiveness. The standard indicators used to assess agricultural interventions, such as adoption, are typically based on farmer self-reports which may be subject to various biases. Understanding the trade-os in improving the precision of agricultural measures through survey design is, therefore, crucial in delivering credible answers.

Recent studies focus on the reliability of agricultural productivity estimates constructed from available developing country surveys. Beegle et al. (2012) randomized interview timing to assess the extent of recall bias on measures of inputs and outputs in Kenya, Malawi, and Rwanda. Consistent with the broader literature on recall bias, they nd that salient events, such as the use of hired labor, and factors of importance, such as fertilizer use, were less subject to recall bias. Deininger et al. (2012) examine the reliability of diaries as a tool for improving measurement of agricultural productivity particularly for crops that are harvested continuously throughout the year. They nd that the output value for continuously harvested crops is systematically under-estimated in standard agricultural surveys.

Our contribution is threefold. First, we document the extent to which self-reported measures of agricultural knowledge and adoption are subject to measurement error. Second, we investigate the determinants of measurement error. We focus on four culprits: response bias, observed respondent characteristics, exposure to training, and recall decay. Third, we assess the cost-eectiveness of 2