Means To Fuel Post-Pandemic Push

Duty on talk-time, debt ease and spared import,
Show the ways of financing post-pandemic revival effort.

As frantic search for financing for post pandemic revival program continues, the next fiscal budget is knocking on the door. There have been reports that tax revenue collection is far below than what was anticipated. Undoubtedly fixing  an economy reeling from the pandemic shock will be a grueling task.

As usual we are going to have budget deficit this year. May be bigger one. Falling tax revenue, shrinking export earnings and remittances make that grim prospect more likely. Generally foreign grants, foreign loan, bank loan and non bank loan play key role in balancing the budget. I did a little analysis to see their role in budget balance. Data were gleaned from BBS Pocket Book 2018 for the period 2008-2018. Following regression function was constructed:

Budget Balance_i = a + b Grant_i + c ForeignLoan_i+ r Bank Loan_i + q Non Bank Loan_i

For 11 observations and 4 explanatory variables, the Durbin-Watson statistic was 1.98, which appeared to have fallen in indecisive zone. Then modified d test was carried out. It turned out that d < d _u (1.98<2.283) or (4-d) < d_u (2.02<2.283). So I ruled out no autocorrelation and concluded there is evidence of autocorrelation. To get rid of serial correlation, I transformed the regression function as follows:

Budget Balance*_i = a + b Grant*_i + c ForeignLoan*_i+ rBank Loan*_i + q Non Bank Loan*_i

Where

  BudgetBalance*_i = BudgetBalance_i - p BudgetBalance_i-1,

Grant*_i= Grant_i -p Grant_i-1,

ForeignLoan*_i= ForeignLoan_i - p ForeignLoan_i-1,

BankLoan*_i= BankLoan_i - p BankLoan_i-1,

NonBankLoan*_i= NonBankLoan_i - p NonBankLoan_i-1

Since in the generalized difference equation I lost the first observation, I took help of Prais-Winsten transformation and transformed the first observations of the variables by multiplying them with square root of (1 – p²) in order to retain them.

 

Then I ran the regression and got the following result:

 

Budget Balance*_i = 2.499 – 3.54 Grant*_i -1.15 ForeignLoan*_i- 0.99 Bank Loan*_i -1.44 Non Bank Loan*_i

(t=1.049, p =0.33, se =2.38) (t=-2.61, p =0.039, se =1.35) (t=-1.77, p =0.126, se =0.646)

(t=-2.33, p =0.058, se =0.426) (t=-3.51, p =0.0126, se =0.411)

(F= 3.94  , p= 0.066)

Except Grant and Non Bank Loan , neither the model nor the coefficients turned out to be significant at 5 % level of significance. They are significant at 10% level of significance. I also noted that standard errors of the generalized difference equation were smaller than the serially correlated regression function, hinting more reliable estimates.

Budget Balance was always negative in the given period. Turning towards  regression result revealed that Grant and Non Bank Loan played a crucial role in the given period to reduce the budget deficit. A 1 unit increase in Grant ( measured as % of GDP) led to 3.54 unit decrease in budget deficit( measured as % of GDP). Meanwhile, 1 unit increase in Non Bank Loan (measured as % of GDP) decreased budget deficit by 1.44 unit. After Non Bank Loan, foreign loan turned out to be major contributor of budget financing.

Despite the fact that our outstanding debt has not crossed the worrying level, it is piling up gradually.

There are other alleys for government to finance its post pandemic economic recovery program. For instance, Bangladesh every year regularly pays millions of dollar as part of its debt service obligation. Disruptions caused by Coronavirus compelled G20 to announce a moratorium on debt service payments until the end of this year, starting from May 1. This is indeed a good news for Bangladesh. In 2018 , it paid $1409.2 million as part of debt service payments. In 2019, it paid $1593.8 million as medium and long term loan repayment.  Clearly Bangladesh will not have to pay this year’s debt payment. This money could be rechanneled to finance the compensation package.

Falling import demand also opens up another avenue for the government to redraw resources to finance its post-pandemic economic scheme. Major primary commodity items like raw cotton and crude petroleum will be less in demand as there is drop in export orders and infrastructure and other* manufacturing come to a stand-still. Similar arguments hold true for major intermediate goods like staple fiber, yarn , petroleum products and capital machinery. The spared import spending could then be reused to facilitate post pandemic economic efforts.

Another popular step, as frequently happened in the past, will be to impose supplementary duty on mobile phone services. This will fetch another thousand  crore Taka.  So without leaning towards costly options like foreign loan, there are ample means to fuel the post pandemic revival drive.

And the lists include:

• Spared BPC subsidy worth Tk 4512.204 crore

• Relaxation of debt service obligation worth at least $1500 million

• Imposition of supplementary duties on mobile services worth at least thousand crore taka

• Drawing forex from spared import spending worth at least one billion dollar

 

As this piece was conceived, Asian Development Bank approved $500 million of assistance for Bangladesh to  deal with post pandemic situation. Similar pledges and grants are on the pipeline. The more they surface, the less likely the chance for costly foreign borrowing.