La Semaine Derniere A Mes Yeux

(17 avril --- 24 avril)

Selon un reportage, 313 cas de contamination au coronavirus parmi les médecins et infirmiers ont été enregistrés au Bangladesh. 11% de cas détectés sont les médecins et les infirmiers. Le ministre de la Santé a jetté une proposition de mettre en place un hôpital pour les élites.

Selon un reportage, coronavirus a tué 263 Bangladais aux pays étrangers. Parmi les morts, 167 Bangladais ont été péris aux États-Unis.

Selon un reportage, Malaisie a fait une requête au Bangladesh de fournir hdroxychloroquine comprimé.

Selon un reportage, jusqu’au vendredi 4.816 personnes sont devenues victims de coronavirus. De plus 127 personnes sont mortes.

Make Good Use Of BPC Subsidy

Falling oil price salvages BPC subsidy,
Retail store sustains consumer activity.
Oil price ushers good news for irrigation,
No evidence of its role in rice price reduction.
Reviving consumer activity and food security
Calls for distribution of spared BPC subsidy.

All-time-low crude oil price extends the spell of profitability for Bangladesh Petroleum Corporation, country’s biggest corporation. Earlier government had provided the much needed fund to subsidize its operation. Higher oil prices made inroads into BPC’s profitability, as evident from the graph. Prior to 2015, BPC regularly incurred loss. Since 2015, it has been treading along the profit-making path. Thanks to oil price less than $70/barrel.

Meanwhile, govt handed out huge subsidy to BPC between 2009 and 2015. The highest was Tk 13557.83 crore in 2013. Back then crude was selling at US$ 108.41/barrel. Since 2015, amount of subsidy has declined to zero. On average govt provided Tk4512.204 crore of subsidy between 2009 and 2015.

Lower oil price relieved the govt from providing huge subsidy to BPC. In the time of pandemic, this is indeed a good news. Salvaged subsidy money could easily be mobilized to help sectors which are in dire conditions. Instead of making frantic requests to other nations for rescuing ailing economy, govt can make good use of this money.

Shops and supermarkets will incur heavy loss, some unsolicited news report says that it will stand at Tk1200 billion, as pandemic lockdowns stall eid shopping activities across Bangladesh. Ramadan and Eid sales jointly account for quarter/half of supermarkets’ annual sales. At the onset of this pandemic, association of shop and grocery owners made frantic plea to govt to give them monetary support. Most of these shops generate employment and act as catalyst to consumerism. Indefinite lockdown makes a dent in their operational expenditure and consumer activity. Many manufacturing and consumer good companies supply them good in the form of credit. Their money also gets locked into coronavirus confinement measures. BPC subsidy money, at least part of it, could be channeled out to help shop owners to meet their operational expenses. The platform of the shop owners could facilitate the distribution of the compensation among the members. Money at the hand of shop owners, in turn, will help clearing the bill of consumer good supplier. So the ecosystem prevailed in the grocery business prior to pandemic will get back into function.

Another sector that can be benefited from the falling oil price and spared BPC subsidy is the agriculture. The winter crop Boro hinges heavily on irrigation. Irrigation consumes lots of fuel. So the irrigation cost will be lower in the wake of lower oil price. By the same token, production cost of urea will be much lower as its key ingredient methane or natural gas is a substitute of crude oil in energy market. LNG prices will be lower in any fall in crude oil price.

However, it is not quite evident whether crude oil price plays any role in influencing the rice price.

I did a little analysis to see whether crude price and Boro production played any role in shaping the price of rice between 2009 and 2018. Data were picked from Bangladesh Economic Review 2018. Durbin-Watson statistic for 10 observations and 2 explanatory variables reported no autocorrelation (d=1.952). Later logarithmic transformation were carried out and regression ran on transformed variables. Result looked like this:

lnRice_t = -44.377-0.17115lnCrude_t+4.950lnBoro_t

(t=-3.62,p=0.008,se=12.20) (t=-1.63,p=0.147,se=0.105) (t=3.94,p=0.005,se=1.254)
(F=8.208, p=0.0146)
where lnRice_t= log natural of coarse rice price at t,
lnCrude_t= log natural of crude oil price at t,
lnBoro_t = log natural of Boro price at t.

Note that crude oil price coefficient turned out to be not significant and negative sign before it calls into question our typical belief.

Boro coefficient, appeared significant in the result, says that holding everything constant a 1% increase in Boro production led to 4.95% increase in coarse price rise in the given period. Well, rice price certainly does not depend on these two variables , there are other factors too. Production of other varieties, food inflation, calamities etc also play a role in shaping price of rice. Inclusion of these variables may yield a meaningful result.

Nevertheless, there will be no denying that part of the saved BPC should also go to provide cash support to the farmers. For instance, the money can be allotted to purchase paddy from farmers at a higher price as part of government’s ongoing rice purchase program. Or it can be used to provide soft agricultural credit. Like the platform of shop owners, agricultural cooperatives can be formed to steer management of the incentive program.

Falling oil price leaves the government some fund, used to give subsidy and finance development expenditure, to cogitate on where to spend them in the time of pandemic. Agriculture and retail stores vie for getting a hold of it. Both are crucial to revive the ecosystem of consumer activity and ensure food security. Instead of swallowing costly bait of foreign credit , govt should make good use of this salvaged subsidy.

La Semaine Derniere A Mes Yeux

(10 avril --- 17 avril)

Selon un reportage, la Banque mondiale s’attend à repli 3% du PIB bangladais. Le minister des Finances s’est insurgé contre la projection. Le Fond monétaire international a baissé la croissance du PIB bangladais. Il attend 2% du PIB l’année prochaine.

Selon un reportage, le gouvernement arête l’opération de vendre denrées de première nécessité à Tk10/kilo. Le dispositive alimentaire a été mis en place pour nourrir les pauvres. Mais corruption et la risqué de contamination a cause assez de polémique dans la presse.

Selon un reportage, le gouvernement a dévoilé un plan de versement de Tk 50 milliards pour aider agroalimentaires, laitiers, aviculteurs et fruitiers.

Selon un reportage, le renseignement afghan a arête deux djihadistes de Daech, don’t un Bangladais. Il s’occupait de l’informatique de IS Khurasan.

Selon un reportage, les ouvriers d’atelier de confection sont descendus dans la rue pour manifester licenciement à cause de coronavirus. Presque 10.000 ouvriers ont perdu leur boulot face au coronavirus.

Selon un reportage, la société Suisse de fabriquant de ciment Holcim a fermé son bureau au Bangladesh pour coronavirus.

Selon un reportage, la police et soldats de l’armée de la mer ont secouru un bateau plein de Rohingya . Le bateau a tenté de traverser la mer pour Malaisie. Mais Malaisie et puis Birmanie ont repoussé le bateau vers Bangladesh.

Selon un reportage, petit-à-petit coronavirus propage à travers de Bangladesh. Jusqu’au vendredi 1838 Bangladais ont été détectés avec coronavirus. &5 personnes ont succombés à la mort.

J’ai du mal à recharger la batterie de mon portable. Ça fait plusieurs jours qu’elle meurt. Avant mon portable comportait bizarrement. Quelquefois il s’élevait lui-même. Quand batterie était pleine, je ne pouvait pas le recharger encore. Je crois que mon portable est tombé victim de hacking.

Grow Crops,Secure Future

Flood causes damage to crops,
Yet leaves a healing message.
Pandemic inflicts more shocks,
But does not leave a recovery passage.
Credit is a must for crop production,
Stop its misuse due to corruption.
Enough food ensures the strength grow more,
And helps winning friends in distant shore.

Coronavirus poses serious obstacle in production and harvest of staple food grain. It already cripples agricultural supply chain. A famine like situation looms large. Though authorities ruled out such an extreme possibility, their reassuring remarks did not find a convinced audience. In urban areas, hoarding fever continues unabated. Desperate people defied confinement measures and stood behind the long queue of fair-price-program, operated by Trade Corporation of Bangladesh.

In the face of soaring rice price, I did a little analysis on production of rice and its dependence on agricultural credit and chemical fertilizers. However, I included the credit and fertilizer on separate equations. And I included both only when I wanted to see their contribution in total production of rice. Data gleaned from Bangladesh Economic Review 2018.

Domestic production of rice means growing of three crops--- Aus, Aman, Boro--- round the year. Data from 1996 to 2017 were considered for current analysis. Following panel model was considered:

Prod_it = b_1i + b₂ Cred_it + e_it

Where Prod_it = production of ith kind of rice at t,
Cred_it= credit disbursement for the production of ith rice at t,
b_1i captures individual heterogeneity.

The issue of whether data would be pooled together with a common intercept or a regression function with dummy variable for individual intercept would be constructed was settled with the aid of F-test. F-test statistic for 2 and 62 degrees of freedom , 263.69, appeared to exceed the critical value, insinuating that different intercepts for different rice varieties.

However in estimating the fixed effect I relied on deviation from individual means. So my model looked like:

῀Prod _it = b῀Cred_it + ῀e_it

Where ῀Prod_it = Prod_it - ‾Prod_i
῀Cred_it = Cred_it - ‾Cred_i
‾Prod_i= mean production of variety i,
‾Cred_i = mean credit for variety i,
‾e_i = mean error for i.

Prior to deviation-from-mean panel model, I checked for autocorrelation for Aus, Aman, and Boro individually. For 20 observations and 1 explanatory variable, none of the crops exhibited any autocorrelation. (For Aus d= 1.411, for Aman d=1.54, for Boro d = 0.801) Having run individual regression, the resulting transformed regressions looked like:

῀Prod _Aust = 0.0345῀Cred_Aust + ῀e_Ausit
(t=4.649,p=0.00017) (F=21.62, p=0.00019)

῀Prod _Amant = 0.2267῀Cred_Amant + ῀e_Amant
(t=4.57, p= 0.00021) (F=20.88, p=0.00023)

῀Prod _Borot = 0.527῀Cred_Amant + ῀e_Amant
(t=8.267, p= 0.000) (F=68.35, p=0.000)

During the given period a Tk 1 crore increase in disbursement of agricultural credit led to increase in Boro production by 0.527 thousand metric ton. Meanwhile, a Tk 1 crore increase in disbursement of agricultural credit translated into increase in Aman production by 0.2267 thousand metric ton.

Later I turned to see what kind of impact disasters leaves for production of rice. Here I took into account natural calamities like flood and cyclone as they inflict severe damage to crop production during the time of their occurrences. A semilogarithmic dummy regression function was constructed and the result looked like this:

lnProd_t = 9.962 + 0.000034Cred_t - 0.0625D_t (t=242.47,p=0) (t=8.23,p=0.00) (t=-1.059, p=0.302) (F=36.11, p=0.00)

Where lnProd_t= natural log of total production of rice at t,

Cred_t = Credit disbursement at t,
D= 1 for flood/cyclone years,
=0 for calm years.

It appeared that dummy coefficient was not significant. If it were significant, we would say that rice production during flood years was 6.06% lower than that of calm years.

Then I probed on joint role of credit and fertilizer on rice production. The resulting function looked like this:

lnProd_t= 8.459 + 0.2445lnred_t- 0.0454 lnChem_t (t=9.771, p=0.00) (t=8.04,p=0.00) (t=-0.346, p=0.732) (F= 94.23, p=0.00)

Where lnProd_t= log natural of total rice production at t,
lnCred_t = log natural of credit disbursement at t,
lnChem_t= log natural of chemical fertilizer at t.
Here coefficient of natural log of chemical fertilizer did not turn out to be significant. Model fit well. We could say a 1% increase in credit disbursement led to 0.244% rise in rice production in the given period.

Crux of the matter is disbursement of credit is vital for crop production. Disaster year presses for renewed effort and commitment in this regard. Disaster like flood often leaves some healing messages for agriculture. For instance, silt deposited along with other agricultural inputs could boost rice production in post flood years. This time we could be deprived of that as damages spring from both pandemic and lockdowns. Silver lining is that oil price is all time low and it means that irrigation cost and fertilizer production cost will be much lower than anyone can anticipate. We have to devise policies to grow more food grain to cater to the demand of people. There is evidence that past pandemic left active population severely weak. And weak population cannot fully contribute to post disaster period.

The post-pandemic world will be hungrier than ever before. Food will play a decisive role in shaping bilateral and strategic relations. We have to grow enough food so that we can win friend and allies in Africa and Asia and secure our economic interests. So we have to grow more food not just for us but for friends in near and far away continents. For that, agricultural credit should be easier to access and hassle-free. And we have to make sure that it falls into the right hands.

Key takeaway of this analysis is that this pandemic may inflict damages to crop production that may not be seen in other disaster years. Agricultural credit is quintessential to grow more crops and requires govt’s policy support. Growing enough food has also strategic benefits. While assessing policies in the time of pandemic, our policy makers should contemplate this uncharted course of food security.

La Semaine Dernière A Mes Yeux

(03 avril --- 10 avril)

Selon un reportage, le plateforme des ateliers de confection, BGMEA, a fermé tous les ateliers après avoir fait polémique en rappellant les ouvriers à Dacca quand l’épidemie propage. En dépit de clôtures, Presque 100 ateliers opèrent à travers du pays. Dirigeants des ouvriers ont dit à la presse, beaucoup d’ateliers n’imposent pas les mesures sanitaires dans atelier.

Selon un reportage, Presque 52 quartiers de Dacca, Tangail et Mymensingh ont fait sujet de mesures de confinement.

Selon un reportage, 200 Bangladais au Singapour sont tombés victims de Coronavirus. Tolarbagh et Bashabo à Dacca, Shibchar à Madaripur, Narayanganj et Sadullapur à Gaibandha ont été declares groupes de lieux plus affectés.

Selon un reportage, 424 Bangladais ont été trouvés avec Coronavirus positive et 27 personnes sont mortes jusqu’au vendredi matin. À l’étranger, environ 140 Bangladais sont morts, don’t 100 péri aux États-Unis.

A Hedge Against Uncertainty In Agribusiness

Corona robs joy of poultry farmer,
Eggs are sold far below market can offer.
Time has come to introduce big buyer,
Way of hedging against loss & not letting him suffer.

Coronavirus stretched its shadow over poultry farming, dairy farming and other agribusinesses. News reports say gloomy dairy farmers are selling their milk much below the market price. Mobile egg sellers are selling eggs at Tk 75/dozen. In normal times, a dozen would cost Tk 120. Evidently, poultry farmers and dairy farmers bear the full brunt of the falling demand, compounded by indefinite lockdown.

Poultry and dairy farming are 100% value adding economic activities. Money was often drawn from local cooperatives, relatives, microfinance institutions and even public banks. Any bad spell to farming activities will augur ill for informal and institutional investors. So in a broader sense, many investors’ money may be lost if poultry and dairy projects fail because of Coronavirus.

If poultry farmers and dairy farmers are not duly compensated for the loss, then we may see a production slump in the subsequent years, adding further woes to the consumers by raising the prices of eggs and milk. Egg is the cheapest source of protein. Any supply shock or price hike in fish or meat leads to consume more eggs. As it appears, this Coronavirus may also make a dent in our protein consumption.

I did a little analysis on the impact of disaster years on egg price for the period 2012-2018. For the given period I gathered data for fish(Rui) and egg prices. Data gleaned from BBS Statistical Pocket Book 2016 and 2018.

At 5% level of significance and for 7 observations and 1 explanatory variable, the Durbin-Watson statistic reported no autocorrelation(d = 2.345).

It was assumed that for ordinary citizens fish and egg secured the bottom places in the protein ladder in terms of price. So, apart from supply and demand side factors egg price to some extent depends on fish price. It was also assumed that eggs were sold at Tk 95 per dozen in 2017 as the data for that year was not available.

Following regression function was constructed:

lnEgg_t = a + b Fish_t + c D_t
where lnEgg_t = log natural of Egg price at t,
Fish_t = Fish price at t,
D = 1 for disaster years ( any kind) ,
= 0 form calm/ normal years.

After running the regression got the following result:

lnEgg_t = 4.97 -0.0012 Fish_t + 0.00616 D_t (F= 1.153, p = 0.402)
(t=18.64, p= 0.000048) (t= -1.48, p= 0.211) (t= 0.117, p=0.91)

Except the intercept, neither the model nor the slope coefficients turned out to be significant. If the coefficient of the dummy variable were significant, we would say that egg prices during disaster years were 0.62% higher than those during calm years.

For the current year, we are witnessing that egg price hits all time low in the last 10 years. Unfortunately, our market conspicuously lacks mechanism of hedging against volatility. Moreover, in a corrupt country like ours compensation for disasters may often fall in wrong hands, mocking the steps to aid victims. As it is noticed, borrowers of microcredit often receive compensation during bad times due to their attachment to institutional lenders. By the same token, if we develop some kind of institution in farming and agribusiness model, then we will ensure just prices for our farmers and will insulate them from any volatility from man-made or natural disruption.

Game theory helps us better to grasp this point. Here I present a sequential game. Pairs of numbers in the game tree represent payoffs to poultry farmer(P) and wholesaler(W). Poultry farmer has two choices to make: to make a contract with an institutional distributor to sell his eggs at negotiated price in the future(C); or not to make the contract with big distributor and rely on the usual middlemen(NC). Meanwhile, for wholesaler, the choice is to offer the prices of normal market(N) or the volatile market (V)reading the market demand.

The first number in the pair represents the price received by the poultry farmer by selling a dozen of egg. The second number represents the payoff to wholesaler by selling a dozen of egg.

Two important criteria for determining the outcome of the game are:

⚫ Provided that what the others have chosen, a player’s decisions must be optimal.
⚫ At the time decisions are taken, they are optimal for the decision-maker.

Looking at game tree, we realize that for two subgames there are two Nash equilibria. If poultry farmer chooses no contract with big distributor, then wholesaler’s optimal decision will be to offer the normal market price. (96,120) is the equilibrium here. Because Tk 120 is greater than Tk 75 for the wholesaler. If the poultry farmer goes for contract with big distributor then wholesaler’s response will be to go for normal market price offer. Here the Nash equilibrium is (108,140).

For poultry farmer, a decision at the present time depends on his returns in the future. He will compare his returns under two states. He will notice that a contract will fetch him Tk 108 and no-contract will get him Tk96. Moreover, volatile prices (Tk 48 > Tk 36) are higher under contract. Since Tk 108 under contract-normal market price is higher than Tk 96 under no-contract –normal market price, his optimal decision will be Tk 108. So poultry farmer looks forward but reasons backward. When poultry farmer chooses the contract, wholesaler will go for the normal-market price, Tk 140 here. So (108,140) is the subgame perfect equilibrium here.

Underlying assumptions here in this discussion are---- there are many big distributors (including the govt backed-one) apart from middlemen; returns under contract with distributors are higher than those under no-contract. Moreover, in any kind of disaster like situation if the govt wants to send compensation then it can do so through the distributors.

Anyone could become this big distributor. Egg cooperatives, TCB, a public listed company or a big local group could easily vie for a big distributor. Govt has to ensure that there are many of these distributors and they operate under certain laws.

Key take-away of this discussion is : big distributors are needed in agribusiness to protect the farmers from volatility and uncertainty. Their presence will ensure just prices for the farmers as well as help flawless distribution of compensation in a disaster like situation.

The idea of big distributors should be preceded by new laws or fine-tuning of existing ones. Laws demarcate do’s and don’ts for the parties in crisis like situation and dispel any ambiguity. Value-adding nature of agribusiness and involvement of informal investors calls for greater govt protection. Laws should be attuned to these ground realities.

La Semaine Dernière A Mes Yeux

(27 mars --- 03 avril)

Selon un reportage, une note faite par l'ONU a fait une projection de 2 millions morts au Bangladesh à cause de propagation du Coronavirus.

Selon un reportage, 269 Américains sont partis Bangladesh dans un vol spécial.

Selon un reportage, 80 Bangladais ont succombé à Coronavirus à l'étranger jusqu'au jeudi, dont 50 Bangladais sont morts aux États-Unis et 19 péri en Angleterre.

Selon un reportage, les tests sérologiques ont affirmé 50 Bangladais avec Coronavirus positive au Bangladesh.

Selon un reportage, Parlement européen a dit non à appel d'annuler GSP sur vêtements bangladais à marché européenne. La décision a porté sourire aux ateliers de confection bangladaise.

Selon un reportage, 498 pèlerins étrangers d'une fraternité musulmane ne partent pas pour leurs pays à cause de propagation de Coronavirus. Ils sont allés en pèlerinage à Dacca à l'occasion de la congrégation annuelle de la fraternité.

Selon un reportage, le gouvernement a commencé le test de dépistage de la Coronavirus dans 14 laboratoires à travers de pays.

Selon un reportage, Economist Intelligence Unit a baissé la projection de la croissance du PIB pour Bangladesh. D'après l'organisation, Coronavirus peut repousser la croissance du PIB au moins de 4%.

Trust The Micro Lenders

Govt backed Social security program ,
Seldom reach village & slum.
Micro lenders doing great job,
Helping borrowers hit by disaster.
Setting shining example in the globe.
Yet calamity hobbles their operation,
Hampering the process of resource creation.

There is little doubt that Coronavirus will leave an anemic economy. There has ,however, been little plans afoot to bring life to vital sectors of the economy with the help of others. Government initiated some local level social security programs without bringing aboard the non governmental organizations. Government-backed social security programs seldom trickle down to target group of people, a view pretty popular among ordinary citizens.

There may be some truth in it. Back in November and December last year, I interviewed 40 rickshaw pullers to grasp well spending and savings behavior of Dhaka rickshaw pullers. When I asked them whether they received any social security benefits from the government, I got three affirmative responses. One got rice from vulnerable group feeding program, another's father received old age benefit and one rickshaw puller's wife got lactating mother's benefit. All three had closer ties with local government representatives: one's relative was union parishod member, the other two had links with ruling elites. So three out of forty rickshaw pullers received government sponsored social security benefits. The forty-respondent strong study may not representative but is an indication how ineffective the government social security program is.

Meanwhile, micro-lending institutions are far more helpful in post disaster periods. In that study, one rickshaw puller, hailing from Borishal, told me one leading microcredit institution gave him, an existing borrower, a calf to recuperate the loss he sustained in Sidr. It is also important to note that a huge section of beneficiaries are women and bottom rung of the society, who generate resources in the economy by raising livestock and sharecropping.

Despite a sustained effort to cast aspersions on microcredit institutions, they are doing a commendable job to scale up the have-nots and accelerate the economy. However, disasters also hobble their operations and seriously harm empowerment of the poor. Microcredit institutions are vital to provide any economic support to the marginalized and vulnerable population.

Recently, I embarked upon to look at disaster year's influence on microcredit operations of three leading microcredit institutions. Data for the period 2005-2018 gathered from Bangladesh Economic Review. Disaster years were political or international or natural disasters that hurt the economy.

Durbin-Watson statistic for ASA and Grameen reported no autocorrelation. For 14 observations and 1 explanatory variable, ASA had a statistic d= 1.695 and Grameen's statistic was d = 1.716. However, for BRAC, it fell into indecisive zone (d = 1.048). Modified d test was found to have positive autocorrelation (d= 1.084< d_u= 1.35).

For ASA and Grameen , following regression functions were constructed:

lnDisb_t = b₁ + b₂Rec_t + b₃D_t

Where lnDisb_t = log natural of disbursement at t,
Rec_t = Recovery at t,

D= 1 for disaster years,
= 0 for calm years.
And for BRAC, following regression function was chosen:

Disb_t = a + b D_t + c Rec_t + d D_t Rec_t
+ u_t

where Disb_t = Disbursement at t,
Rec_t = Recovery at t,
D= 1 for disaster years,
= 0 for calm years.
and u_t was generated through AR(1) scheme:

u_t = u_t-1 + e

Since BRAC data had positive correlation, transformed function was constructed. From known P, I derived (Disb_t - PDisb_t-1) as regressand and (Rec_t - PRec_t-1) as regressor. This approach was resulted in loss of 1 observation for both. Prais-Winsten transformation (√1-P² Disb_t and √1-P² Rec_t ) was done to prevent it. For calm years, values of D were zero. But first observation of disaster years was set 1/(1-P) and 1 for the rest of the disaster years. D_t Rec_t
was zero for the calm years. First observation for disaster years was assigned D_t Rec_t
= Rec_t and all observations were assigned (D_t Rec_t - D_t Rec_t-1) = ( Rec_t - P Rec_t-1)
The resulting functions appeared to be:

ASA: lnDisb_t = 8.99 + 0.0000067Rec_t - 0.144D_t (F= 2.588, p= 0.12) (t=35.70, p=0) (t=2.27, p= 0.043) (t= -0.42, p= 0.67)
Grameen: lnDisb_t = 9.083 + 0.00012Rec_t - 0.0038D_t (F= 67.85, p= 0.0)
(t=73.07, p=0) (t=11.53, p= 0.00) (t= -0.038, p= 0.96)
BRAC: Disb_t = -0.506 - 37.214 D_t + 1.112 Rec_t + 0.0037 D_t Rec_t (F= 506.9, p= 0)
(t= -0.001, p= 0.99) (t=-0.125, p=902) (t=18.63, p=0.00) (t=0.061, p=0.95)

The model fit well for BRAC. However, differential intercept and differential slope coefficients were found to be insignificant. Had the differential intercept coefficient been significant, we would say that BRAC's disbursement of microcredit during disaster years was lower by Tk 37.214 crores.

Regression model for Grameen fit well at 5% level of significance, as reported by F. Meanwhile, it did not fit well for ASA at that level of significance. However, slope coefficient for dummy variable for both the model did not appear to be significant. Had it been significant, we would say Grameen's disbursement for disaster years was 0.38% lower than that of normal years and ASA's disbursement for disruptive years was 13.45% lower than that of normal years.

It is evident that disruption resulting from various forms of disasters has harming effect on microcredit operations. This may affect economic activities of have-not communities.

Since microcredit institutions scattered all across country and they have a large borrowers' base, post disaster efforts will be better implemented with their help. Misappropriation will be lower if the fund is distributed through them. At the same time, more government money should be injected into microcredit institutions so that microcredit operations, or economic activities of the have-nots, do not get affected by Coronavirus. Money at the hands of Have -nots and marginalized groups means resource creation, leading to increase of GDP. And microcredit institutions are leading the way in terms of resource creation.