Devalue Currency To Augment Demand

Taka loses fast its value against dollar,
Reasons put forward for paying the bills of importer.
Increase in money supply depreciates local currency,
Devalued taka augments demand, output and local vacancy.
Overshooting exchange rate may approach stable value,
Lowering interest rate is a must amid pandemic flu.

A recent news report (May 20)says there has been a dollar crisis. To meet the growing import bill amid sluggish export, demand for dollar surged. Taka against dollar has been depreciated to Tk 88.50 at the banks. This is happening when government doled out Tk 5000 crore credit to RMG owners to clear dues of workers. In addition, government assured cash benefits to rural poor and other incentives to various sectors. By the time I am writing this piece, remittances in the month of Ramzan have reached $1.09 billion.

I embarked upon to see what impact an increase in M2 would leave on exchange rate. M2 comprises of currency outside bank, demand deposits, narrow money supply and time deposits. Data were taken from Bangladesh Economic Review 2018 for the period 1996-2018.

Autocorrelation check for 23 observations and 1 explanatory variable reported positive correlation (d = 0.374). I did not transform the data. It was assumed that during the unit root test inclusion of lagged residuals will take care the autocorrelation.

Then I went for unit root test to see whether exchange rate and M2 were stationary. To bare eyes, it appeared that both the variables wandered around a trend. So I constructed the following regression equations:

🔺 Exch_t = a + bt + c Exch_t-1 + d 🔺 Exch_t-1
🔺 M2_t = a + bt + c M2_t-1 + d 🔺 M2_t-1
Where 🔺 Exch_t= Differences in exchange rate at t,
Exch_t-1 = exchange rate at t-1,
🔺 M2_t= Differences in M2 at t,
M2_t-1= M2 at t-1,
🔺 M2_t-1= Differences in M2 at t-1,
t = a time trend variable, here year.

After the regression run , I obtained the following result: 🔺 Exch_t = -1778.34 + 0.902t -0.501Exch_t-1 + 0.455 🔺 Exch_t-1
(t=-2.52, p=0.022, se=706.22) (t = 2.53, p=0.022, se=0.36) (t=-2.79, p=0.012, se=0.18) (t=1.97, p=0.065, se=0.230)
(F=3.39, p=0.042) 🔺 M2_t = -7176664 + 3590.12t + 0.0028M2_t-1 + 0.373 🔺 M2_t-1
(t= -2.59, p=0.019, se=2774933) (t=2.59, p=0.019, se=1386.81) ( t= 0.088, p= 0.93, se=0.0313) (t=1.27, p=0.22, se=0.29)
(F=67.54, p=0.00)

Huge standard errors put question mark on the intercept and trend coefficient of 🔺 M2 function. Tau statistics of slope coefficients of lagged exchange rate and M2 , -2.79 and 0.88 , in absolute terms were smaller than MacKinnon critical tau statistics at 5% level, -3.4620. So I did not throw away the null hypothesis that c=0 or exchange rate or M2 are nonstationary.

As the first differences of these two variables appeared to be nonstationary, it was assumed , for the sake of simplicity that they were integrated on order d,I(d). Regressing exchange rate on M2 , I obtained the residuals for cointegration test. Then I ran the following regression:

🔺 resid_t = b resid_t-1 + c 🔺 resid_t-1

And the result was: 🔺 resid_t = -0.160 resid_t-1 + 0.51 🔺 resid_t-1

(t=-2.012, p=0.058,se=0.079) (t= 2.84, p=0.010,se=0.18)

(F=5.85,p=0.011)

The computed tau statistic -2.012 was greater than the critical value -3.37% at the 5% level of significance. I did not reject the null hypothesis that least squares residuals are not cointegrated. Cointegrated Regression Durbin Watson (CRDW) test also validated the claim . The computed d = 0.374 turned out to be smaller than the critical value 0.386 at 5% level of significance. So I did not reject the hypothesis that exchange rate and M2 are not cointegrated.

In this particular situation, exchange rate and M2 were I(d) series and not cointegrated. So I went for a VAR model:

🔺 Exch_t = b₁🔺 Exch_t-1 + b₂ 🔺 Exch_t-2+ b₃🔺 M2_t-1 + b₄ 🔺 M2_t-2+ v^🔺Exch_t

🔺 M2_t = c₁ 🔺Exch_t-1 + c₂ 🔺 Exch_t-2+ c₃ 🔺 M2_t-1 + c₄ 🔺 M2_t-2+ v^🔺M2_t

VAR model did not fit well (🔺 Exch chi² =6.88, p= 0.144, and for 🔺 M2 chi²= 142.85, p=0.00). Nevertheless, I wanted to see the Impulse Response Function (IRF) that shows effect of a shock of endogenous variable on itself and other endogenous variables. An increase in orthogonalized shock to M2 resulted in a short decrease ( depreciation of Taka ) in the exchange rate that withers away 1 period later.

Though the VAR model is to be accepted with a dollop of salt, this is pretty much in line with theory found in economic text book. Temporary drop in global demand shifts the DD schedule, which shows mixes of output and exchange rate for keeping output market in equilibrium in the short-spell, to the left. This in turn reduces full employment-level output to a lesser level, provoking depreciation of currency. A currency depreciation augments both aggregate demand and output at home. Meanwhile, increase in money supply in the domestic market depreciates exchange rate and causes AA schedule, which links exchange rates and output levels to keep the money and foreign exchange markets in equilibrium, to shift upward. Domestic goods become more competitive in global market , triggering a rise in domestic output and employment. For a given level of output, an increase in money supply can cause exchange rate to overshoot its long-term exchange rate for a while. One may argue that since our import surpasses our export and in this time of falling export earnings a depreciation may erode our current account balance. Point is that economic theory says for a brief period there may be a dent in the current account balance (ours a negative) but in the long run it will definitely improve.

Point is currency depreciation is good for our economy and wild fall in Taka may approach its long-run value with the course of time. To revive the falling demand, government can do more apart from doling out incentives. One step can be to lower the domestic interest rate in a bid to increase the money supply.

Oil Price And Current Account Balance

Could drop in oil price augur good for economy?
Searched the answer spending hours many,
Data on current account and crude oil price
Revealed an unpleasant surprise.
Contrary to belief, current account sustained deficit
Slide from $70 may also hurt forex receipt.
IRF says oil price shock has lasting effect,
This time, positive outcome is what I expect.

In international market, crude oil price hit a nadir after two leading producers had failed to reach agreement on production level.

A local news report says it augurs good for Bangladesh Petroleum Corporation, Bangladesh’s biggest corporation with annual turnover of Tk 250 billion, since government will no longer have to subsidize its operations and it will again walk along the profit-making path.

Lower oil price also means cost of import and cost of production will be much lower. This is happening when aggregate demand in the world market is falling. Investment and infrastructure projects are being postponed. However, export orders are also being called off.

I was keen to look at what it means for current account balance (CAB), which registered negative for the last couple of years. I gathered the old crude oil price data from my earlier analysis on BPC profit/loss, delving macrotrend and updated it for $33 / barrel in 2020. I gleaned the data on CAB from Bangladesh Bank website. Data for 2020 were only available for July-December period.

Since crude oil price influences import and export item prices, it is assumed that current account balance depends on crude oil price.

A quick look at the data revealed that between 2010 and 2020, economy witnessed current account deficit when the crude oil price was well below the $70/barrel, a much talked about price to sustain the economies of Middle East. It is contrary to the belief that a fall in crude oil price improves current account balance. I am still in that group of believers. It is also important to note that Bangladesh embarked upon big infrastructure and investment projects in the given period. Maybe that is the reason for big current account deficit. As I was interested to see the impact of crude oil price on CAB, I needed to fit a model.

Source: Bangladesh Bank & Macrotrend

First, I carried out some diagnostic Check. Time series data called for autocorrelation check. Durbin-Watson statistic (d=1.22 for 11 observations and 1 explanatory variable) fell into indecisive zone. So I went for modified Durbin-Watson check. It reported positive autocorrelation( d=1.22 < d_u = 1.324).

However, I did not transform the regression to make it generalized difference equation. I worked on the serially correlated data and checked for stationarity. To check for stationarity, following regressions were constructed:

🔺 CAB_t = a + b CAB_t-1 + ct + d 🔺 CAB_t-1
🔺 Crude_t = a + b Crude_t-1 + ct + d 🔺 Crude_t-1
Where 🔺 CAB_t= Differences at current account balances at t,
CAB_t-1 = current account balances at t-1,
🔺 Crude_t= Differences at crude oil prices at t,
Crude_t-1= crude oil price at t-1,
🔺 Crude_t-1= Differences at crude oil prices at t-1,
t = a time trend variable, here year.

Tau statistics of slope coefficients of lagged CAB and Crude, -2.33 & -2.3 , in absolute terms were smaller than ADF critical tau statistics at 5% level, -3.4620, and at 1% level , -4.067. So I did not reject the null hypothesis that b=0 or CAB and Crude show an unit root or they are nonstationary.

Please note that first differences of CAB and Crude did not turn out to be stationary. I did not have patience to difference further and to see at what level they became stationary. So both CAB and Crude, for the sake of simplicity, were integrated of order d, I(d).

To check for cointegration, I first regressed CAB on Crude and got the residuals. Then I ran the following regression:

🔺 resid_t = b resid_t-1 + c 🔺 resid_t-1

At 5% level, critical value , reported in J Hamilton’s Time Series Analysis was -3.37. Since computed -2.79 was greater than -3.37, I did not reject the null hypothesis of no cointegration or residuals are nonstationary.

In this case, CAB and Crude were I(d) series and were not cointegrated. So, I went for a VAR model :

🔺 CAB_t = b₁ 🔺 CAB_t-1 + b₂ 🔺 CAB_t-2+ b₃ 🔺 Crude_t-1 + b₄ 🔺 Crude_t-2+ v_t^🔺CAB

🔺 Crude_t = c₁ 🔺CAB_t-1 + c₂ 🔺 CAB_t-2+ c₃ 🔺 Crude_t-1 + c₄ 🔺 Crude_t-2+ v_t^{🔺 Crude}

VAR model did not fit well as reported by F( for 🔺CAB F= 0.8960, p= 0.54 and for 🔺Crude F= 0.048 , p= 0.99). However I was keen to see the Impulse Response Function(IRF), which shows the effect of a shock to an endogenous variable on itself and on other endogenous variables.

An orthogonalized shock to Crude was reciprocated once or twice by CAB and it died out seven or eight periods later, as shown in the graph. The effect of Crude oil price shock on CAB did not wither away instantly and lasted for quite some time.

Analyzing the data for the last 10 years, it was noticed that Bangladesh sustained current account deficit for the last couple of years when the oil price was well below $70/barrel. However, current account deficit deteriorated when the crude oil price increased. Check the price rise when $86/barrel became $107/barrel in 2011, $53.72/barrel rose to $55.71/barrel in 2017 and $55.71/barrel increased to $66.87/ barrel in 2018. Two things became clear: first, increase in crude oil price evidently hurt current account balance; second, price below $70/barrel did not always generate a current account surplus.

My understanding of the situation is that prices lower than $70/barrel stall many investment and construction projects in the Middle Eastern countries where many Bangladeshis work. As construction work halts , they may be laid off. Remittances, rescuer of current account balance , may also get affected. In addition, higher oil prices generate revenue for investment in many of the occidental countries, contributing to increase in household income. That means more spending on apparel items , leading more orders for Bangladeshi garment factories. This may not last as that high oil price driven revenue may dry up , hurting investment and household income in those countries. So our apparel export may also take a hit because of this. By the way, this is considered without taking into account the Corona effect.

And from the graph it was seen that any rise or fall in Crude oil price had a lasting effect on the current account balance. Could it be different for this time?