rafmacalaba/datause-encoder-data huggingface dataset:
25 both by economic contraction (mean income in the PNAD sample fell from R$332 in 1981 to R$316 in 1993) and by rising inequality, but rising inequality was the dominant force. The redistribution component was the larger force behind increasing poverty between 1981 and 1993, across all poverty lines and measures, and its power was greatest for the most bottom-sensitive poverty measures, the poverty gap and FGT(2).

With the advent of economic stability, both components changed sign. From 1993 to 2004, both growth and falling inequality contributed to declining poverty although, this time, the growth component dominated. Of the ten-point decline in poverty incidence, over six points are accounted for by growth, with redistribution responding for 3.5 points. The redistribution share does improve for FGT (1) and (2). Looking at the whole 1981-2004 period, there was a net decline of some seven percentage points in poverty incidence, five of which are attributable to growth, and two to redistribution.<sup>32</sup>

# **5) The Impact of Macroeconomic Performance.**

The dynamic decompositions in the previous section shed some light on the changes in Brazilian inequality and poverty over the last two and a half decades. In particular, a convergence in mean incomes between urban and rural areas; a reduction in average returns to education; and possibly a decline in inter-racial disparities seem to account for at least part of the decline in inequality during 1993-2004. As we learned from the decomposition by income sources in Section 3, larger volumes of better-targeted social assistance transfers may also have contributed.

But the picture was less clear for the increase in inequality during 1981-1993, when changes in the distribution of education appear to account for only a small part of the substantial overall increase in inequality, and the other decompositions fail to explain much.<sup>33</sup> Bearing in mind that the outstanding economic fact of the 1980s in Brazil was macroeconomic instability and, in particular,

> 32 The sign of the redistribution component in the 1981-2004 decomposition flips across the two poverty lines, suggesting that the manner in which one accounts for differences in the cost-of-living in different regions, and between rural and urban areas, will affect one’s interpretations of the impact of falling inequality on poverty.

> 33 A counterfactual micro-simulation analysis of the 1981-1996 period (in Ferreira and Paes de Barros, 1999) broadly confirms the suggestive evidence from Table 5: changes in the composition of education in the labor force were the main observable force behind rising inequality. Returns to education were falling, and contributing to a decline in inequality. Returns to experience, on the other hand, were rising and contributing to greater inequality. Even in that much more disaggregated – and exclusively urban – analysis, however, an unexplained gap remains for
# **4. Implications for policy**

The analysis conducted so far has highlighted some factors that may affect the provision of inter-firm trade finance, trying to stress those that raise greater concern in times of crisis. This section will focus on some policy instruments which could be devised to address these concerns.

# **_4.1 Improving information sharing_**

Some literature – both theoretical (Biais and Gollier, 1997) and empirical (MacMillan and Woodruff, 1999; Johnson _et al._ , 2002) – has rationalized the use of trade credit with an information advantage the supplier has over other creditors regarding the buyer’s creditworthiness. This advantage may descend from existing business relationships or from prior investigations on the customer’s reliability, for example through mechanisms of information sharing.<sup>16</sup> In a crisis scenario in which banks are more concerned about credit risk and less willing to extend credit, these two factors may be crucial to limit potential damage and prevent that the shortage in trade finance adds to the downturn in demand. In particular, relevant benefits may be gained from improving cross-country information sharing mechanisms, for example by extending public credit registries and voluntary exchange mechanisms to developing countries, where these systems are often still being designed, and promoting the sharing of this information across trading countries.

# **_4.2 Exploiting traded goods characteristics_**

The discussion in Section 3.1 has confirmed that inter-firm trade financing presents some advantages over other lending relationships related to the characteristics of traded goods. These may prove important as they may suggest specific segments for intervention in the current credit crunch.

The literature has in particular provided some empirical support for the moral hazard hypothesis. This predicts that firms selling (buying) standardized goods should offer (receive) less trade credit. The intuition is that defaulting on suppliers of these goods may involve low costs, as the suppliers are easy to replace, or high benefits, as the traded goods have high diversion value.

It is therefore plausible that the problems brought about by the financial crisis be particularly exacerbated for these firms that are not shielded from moral hazard problems. Raising credit may be harder for them, more so during a financial crisis.

> 16 By acquiring information about repayment history of the customer across a range of suppliers, the seller increases the information on which to base its credit extension decision. Kallberg and Udell (2003) show that trade credit history in Dun&Bradstreet reports improves default predictions relative to financial statements alone. For the role and effects of information sharing in credit markets, see Jappelli and Pagano (2005, among others).

15
# **I. Introduction**

Despite improvements in Africa’s growth performance since 2000 (see, e.g., Devarajan and Fengler, 2013), its history of economic performance had long been disappointing and was even described as a tragedy by some commentators (Easterly and Levine, 1997). Although less welldocumented and perhaps not surprising, the financial sectors of Sub-Saharan African countries remain woefully under-developed, even relative to the standards of developing countries. This is despite the fact that most of these countries have undergone extensive financial sector reforms in the last two decades of the same proportions as other developing and emerging countries.<sup>1</sup> The financial development gap in Sub-Saharan Africa is stark, and the gap is visible in the data. For example, the population-weighted trends for developing regions in terms of liquid liabilities and private credit (both divided by GDP) show that the rest of the developing world has seen substantial improvement relative to Africa in the last two decades, though the patterns differ across regions. Based on the pre-crisis data, the liquid liabilities of African financial sectors averaged below 30 percent of GDP in 2007 (see Table 1). In no other region of the developing world did that figure stand below 40 percent. The credit side of the picture looked even worse: private credit averaged 17 percent of GDP in Africa in 2007, compared with ratios ranging from 33 to 44 percent for other developing regions. These pre-crisis data show that the financial development indicators of Africa improved in the period 1995-2005, but at a much slower pace than in other developing and emerging countries in Asia, Eastern Europe, Latin America, and the Middle East.

The poor state of African financial development raises a number of important questions as to what went wrong with the financial reforms in Africa and what could be improved. Is African financial development slow in itself, or is it a reflection of broader economic and policy failures?

> 1  The reform packages included price and interest rate liberalization, removal of credit ceilings, introduction of a variety of measures for banking and capital market development, including financial regulatory schemes, and large scale privatizations of state-owned enterprises (see, for instance, Nissanke and Aryeetey, 1998; Senbet and Otchere, 2006; and Honohan and Beck, 2007).

2
A substantial amount of research has been done on the impact of the financial system on economic outcomes since the 2008 financial crisis. Attention has mostly been focused on the financial system’s contribution to productivity, innovation and growth on the one hand, and to the nature of recessions accompanying financial busts on the other. Related to the latter strand of study is the impact of financial sector activities on economic volatility, another area that has been of interest. The benefits of deep financial systems in supporting growth has long been recognized in both theoretical and empirical economics. Policy makers have supported enhanced access to credit for households as well as firms, with a view to support consumption smoothing and investment decisions by households. More recently, research has focused on whether finance in all forms supports growth and whether fast growing financial sectors support growth in all contexts or only under certain conditions. Researchers have asked whether certain financial sector activities should be constrained or regulated differently or whether growth of overall credit should be slowed because (a) the resource allocation that occurs in certain contexts is not productivity or growth enhancing, or (b) because the economywide cost risks associated with financial activities outweigh the benefits of individual risk-taking.

This paper examines whether credit to different types of borrowers, namely, households and firms, has differential effects on external balances. The reason for the differential effects would spring from the presumption that households and firms tend to borrow for distinct purposes. Households primarily borrow for consumption<sup>2</sup> while firms would borrow for production, part of which might be exported. In the first instance, therefore, trade balances would tend to be more negatively affected by consumer credit, while export shares to GDP would not be affected, or would be affected negatively if credit is diverted to imports for consumption. Part of firm credit may support export related activities, though overall, the effect is ambiguous. Rising credit may affect domestic demand to such an extent that the export facilitating effect is subsumed by the import effect.

This paper builds on recent research that examines the link between financial systems and economic outcomes by extending the types of outcomes affected by finance and also by distinguishing by borrower type. The paper uses panel data covering 42 countries over the period

> 2 Though they may “borrow” to purchase other financial assets.

2
problems across countries in terms of the survey instruments used. The Estonia and Poland data sets document in great detail the employment dynamics experienced by these countries between 1989 and 1995, using both official government data and information collected through a labor force survey.

# **Responses to Crises and Institutional Changes**

Following the transition from a planned to a market economy, Eastern European and fonner Soviet countries experienced a larger-than-expected decline in aggregate activities. Recent important studies have looked for causes of this output collapse. _Ex ante,_ researchers agreed that output may initially decline before resuming its growth as the market reallocated resources from less to more productive uses. Borensztein and Ostry (1995) hypothesize that the sharp fall was mainly the result of a supply side shock: as prices were liberalized, state owned enterprises were unable to pay for inputs. Commander and Coricelli (1992), and Borensztein, et al. (1993) emphasize a demand shock: the increase in prices reduced the domestic demand for final goods. Berg (1994), Atkeson and Kehoe (1996), and Shimer (1995) argue that structural adjustments related to the transition itself were the main cause of the initial decline. Finally, Murphy, et al (1992) and Shleifer and Vishny (1993) focuse on the political economy of the transition process and emphasized the perverse effects of a partial price liberalization reform and government corruption.)<sup>3</sup> The World Bank coverage of output behavior in transition economies is somewhat limited and unsystematic across countries, hampering cross-country analysis. I]n addition, the country-specific analyses are based on firm surveys designed to test specific hypotheses, preventing researchers from evaluating competing hypotheses even within the same country. Nonetheless, existing surveys have provided us with great insights into the effects of transition on output.

> 13 Estrin, Schaffer and Singh (1993) offer new insights on the structural restructuring process that naturally accompanies a change in regime for some Eastern European countries by integrating their industry-level analysis with firm-level data. Their exploration suggests that the process of industrial adjustment across a few Eastern European countries has been remarkably similar, and that the speed at which reforms are introduced affects enterprise profitability. Pinto, Belka and Krajewski (1992) complement Estrin et al. (1993)'s results with a study of the state enterprises in Poland before and after the first round of reforms. Their analysis reveals that firms, helped

22
– Table 3: Baseline Treatment Effect Estimates Spatial Matching

|||40 km bufer|||60 km bufer||
|---|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|(6)|
|1st FO tenure (_α_1)|0.0465***|0.0463***|0.0500***|0.0427***|0.0424***|0.0441***|
||(0.0089)|(0.0089)|(0.0087)|(0.0087)|(0.0088)|(0.0086)|
|2nd FO tenure (_α_2)|0.0430***|0.0429***|—|0.0280**|0.0278**|—|
||(0.0162)|(0.0162)||(0.0139)|(0.0139)||
|_p−_values:|||||||
|_H_0 :_γc_ = 0|0.000|0.000|0.000|0.000|0.000|0.000|
|_H_0 :_α_1 =_α_2|0.845|0.851|—|0.367|0.371|—|
|_R_<sup>2 </sup>(within)|0.598|0.598|0.599|0.567|0.567|0.567|
|Observations|223,109|222,970|222,508|674,296|674,121|673,517|
|Number of clusters|751|751|751|916|916|916|
|Number of FOs|302|302|302|348|348|348|

_Notes:_ Robust standard errors in parentheses (*** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1), clustered on FO/distributary (distributary for non-FO channels). Dependent variable is tail shortage _DPR_<sup>_H_</sup> _− DPR_<sup>_T_</sup> . All specifications include channel fixed effects, buffer-year fixed effects, and circle-specific time trends (coefficients on which are _γc_ ). Guide to specifications: (1,4) All channel-years; (2,5) Drops cases of FO tenure extended by court-stay; (3,6) Drops all channel-years in second FO tenure.

# **4.4 Spatial matching results**

The spatial matching strategy yields similar estimates of the first FO tenure treatment effect regardless of whether we adopt a 40 km (Table 3, column 1) or a 60 km (column 4) buffer radius. Relative to the pre-reform scenario in FO circles, the first tenure effects imply a 51% (40 km buffer) and 46% (60 km buffer) increase in tail shortage. The second FO tenure effects here are statistically significant and of similar magnitude to the first tenure effects, so that we cannot reject the equality restriction _α_ 1 = _α_ 2. Moreover, none of these results depends on the inclusion of the potentially suspect observations involving court stays (cols. 2 and 6). Finally, Table 3 reports specifications that that drop channel-years in second FO tenures altogether (columns 3 and 6), which has little impact on the first tenure coefficient.<sup>19</sup>

> 19Equality of circle-specific time-trends can be rejected in all specifications. Note, as well, that dropping observations from 2006, thereby rendering parallel the pre-trends in FO and non-FO circles (see fn. 16), does not appreciably affect our results (the estimate of _α_ 1 in specification (4) falls to 0.041 (0.009) and that of _α_ 2 falls to 0.022 (0.014)).

26
# 8. References

Alongi, D.M. (2002). Present state and future of the world’s mangrove forests. Environ. Conserv. 29, 331–349.

Awal, M.A.; Islam, A.F.M. (2020). Water Logging in south-western coastal region of Bangladesh: Causes and consequences and people’s response. Asian J. Geogr. Res, 3, 9–28.

Best, Ü.S.N., Van der Wegen, M., Dijkstra, J., Willemsen, P.W.J.M., Borsje, B.W., Roelvink, D.J.A., (2018). Do salt marshes survive sea level rise? Modelling wave action, morphodynamics and vegetation dynamics, Environmental Modelling & Software 109: 152-166, Bao, T. (2011). Effect of mangrove forest structures on wave attenuation in coastal Vietnam. Oceanologia. 76. 10.5697/oc.53-3.807.

Bhowmik, A., Cabral, P. (2013). Cyclone Sidr Impacts on the Sundarbans Floristic Diversity. Earth Science Research. 2. 62-79. 10.5539/esr.v2n2p62.

Bricheno, L.M., Wolf, J., Islam, S., (2016). Tidal intrusion within a mega delta: An unstructured grid modelling approach. Estuarine, Coastal and Shelf Science 182, 12-26.

Carrol, C.A., Bunting, P., Hardy, A., Bell, G. (2019). Using Continuous Change Detection and Classification of Landsat Data to Investigate Long-Term Mangrove Dynamics in the Sundarbans Region. Remote Sens. 2019, 11(23), 2833; <u>https://doi.org/10.3390/rs11232833</u> Dasgupta, S., Huq, M., Khan, Z.H., Zahid Ahmed, M.M, Mukherjee, N., Khan, M.F., Pandey, K. (2014). Cyclones in a changing climate: the case of Bangladesh, Climate and Development, 6:2, 96-110, DOI: 10.1080/17565529.2013.868335 Dasgupta, S., Islam, M.S., Huq, M., Khan, Z.H., Hasib, M.R. (2017). Mangroves as Protection from Storm Surges in Bangladesh. Policy Research Working Paper 8251.

Dasgupta, S., Sobhan, I., & Wheeler, D. (2017b). Impact of Climate Change and Aquatic Salinization on Mangrove Species in the Bangladesh Sundarbans. Vol. 46, No. 6, 680-694.

Eckstein, D., Künzel, V., Schäfer, L., Winges, M. (2020). Global Climate Risk Index 2019. Germanwatch e.V.

Etminan, V., Lowe, R., Ghisalberti, M., 2019. Canopy resistance on oscillatory flows. Coast. Eng. 152 https://doi.org/10.1016/j.coastaleng.2019.04.014.

28
environmental judges).

A key challenge for the SPCBs in enforcing the regulations is the lack of civil administrative authority (particularly, to impose administrative fines) which limits the effectiveness of their enforcement efforts and leads to over-reliance on the judiciary for enforcement. Filing criminal cases against violators in trial courts or reacting to PILs is a time-consuming, unpredictable, and ineffective enforcement mechanism. Criminal cases brought by SPCBs often have a low conviction rate (although that varies greatly between the states). Significant human and technical capacity constraints are also factors in terms of the effective execution of all compliance and enforcement related functions, especially at the state level.

Currently, India requires industries to monitor some compliance parameters through selfreporting. But that information is used only as an indicator of compliance. The government does not utilize it as direct evidence of a violation in the courts. Instead, the government relies solely on legal samples that are resource-intensive and time-consuming to collect; are frequently challenged for procedural deficiencies; and often are not representative of a facility’s compliance status. Shifting the burden of compliance monitoring away from the government to the regulated community would enable the government to evaluate and determine compliance for a larger number of regulated sources on a more frequent basis in a more cost-effective manner (USEPA, 2005).

# **3 Data and Descriptive Statistics**

## **3.1 Data**

The data for the study were obtained from the Odisha State Pollution Control Board (OSPCB) for 150 key large and medium firms for the period 2009-2014. The board assesses compliance by a firm through onsite inspections as per the Air Act and Water Act. All large and medium firms and red category small-scale firms are inspected at least once every six months and once a year, respectively. OSPCB inspectors carry out two main types of inspections: (i) compliance evaluation inspections where a firm’s pollution control facilities, monitoring methods, and records are examined, which amounts to verification of initial compliance by a firm, and (ii) compliance sampling inspections where air/water samples are collected onsite. Pollution control devices and testing procedures with the firm (if any) are also inspected. Such inspections check for continuing compliance by a firm.

7
# **II.** Export-Led Growth: The Evidence

The superior performance of countries pursuing an ELG strategy is well documented in many comparative studies sponsored by the OECD, NBER, and World Bank.' From this literature, a number of suggestive "stylized facts' have emerged.

First, countries undergoing ELG have industrialized by achieving high growth rates, increasing trade shares in GDP, and dramatic structural change. As documented in Chenery, Robinson, and Syrquin (1986), countries pursuing ELG strategies had rapid structural changes characterized by: (1) rapid increases in the use of intermediate inputs ("deepening" of their input-output structure) and (2) unbalanced growth led by increased demand for tradable goods. Typically, the early phase of ELG industrialization is led by light manufacturing, followed by development of the intermediate and capital goods sectors.<sup>2</sup> Second, there is an acceleration in the rate of economic growth during the transformation associated with industrialization.<sup>3</sup> There is a positive correlation (at the economywide level) between aggregate growth and TFP growth. One common explanation for these observations is that there is continuing dynamic disequilibrium adjustment in the tSee comparative case studies by Little, Scitovsky, and Scott (1970), Balassa and Associates (1971, 1982), Bhagwati (1978), and Chenery, Robinson, and Syrquin (1986). Cross-country correlations between export growth and aggregate growth are presented in Michaely (1977), Heller and Porter (1978), Balassa (1978), Feder (1983), and Jung and Marshall (1985).

2See Chenery, Robinson, and Syrquin (1986), chapters 3, 6, and 7. Balassa (1979) descrbes these phases in terms of 'stagee of comparative advantage. See also de Melo (1985), who compares Korea and Taiwan.

3Evidence in support of the acceleration hypothesis during the industrialization of today's developed countries is given in Kuznets (1971). Evidence for today's developing countries is reviewed in Syrquin (1986).

-3-
Or, in more general terms:

# (9) Qh = qh( e, T)*(GDP/Ph).

In general one would expect a non-positive sign<sup>on the</sup> effect of e on Qh and an ambiguous sign with respect<sup>to T. This</sup> should not bother us since those signs will be empirically<sup>tested</sup> later in this Section.

The treatment of the Demand side is similar to that<sup>of the</sup> supply, except that demand for the Non-Traded Good (Ch)<sup>should</sup> not depend on GDP, that is the value of domestic production<sup>of</sup> goods, but on Absorption, that is the value of domestic expenditure on goods. Denoting absorption by A,<sup>we can express</sup> the demand for Ch as:

- (10) Ch = ch( e , T )*(A/ph)

We finally use the basic national accounts relationship,<sup>that</sup> gives rise to Alexander's Absorption Approach:

- (11) GDP = A + TS ,where TS is the Trade Surplus.

Market equilibrium requires the equality of Qh and Ch:

- (12) Qh = Ch

Substituting (9),(10) and (11) into (12) we obtain:

- (13) qh(e,T)*(GDP/Ph)= ch(e,T)*(GDP-TS)/Ph

Finally, denominating ts= TS/GDP to the ratio of<sup>the Trade</sup> Surplus to GDP, we obtain:

- (14) qh(e,T)= ch(e,T)*(1-ts).

28