The finale for the buzzing-B word which was hitting the headlines for the past fortnight has come to an end. The nail biting event anguished which the entire nation cataloging from the ubiquitous taxpayers to the investment giants.
Lets take a sneak peek into the quintessential strands in the ANNUAL FINANCIAL STATEMENT of the UNION BUDGET. The highlighted branches under the canopy of annual financial statement are
- Capital Account Receipts
- Capital Account Disbursement
- Revenue Account Receipts
- Revenue Account Disbursement
- Public Account Receipts
- Public Account Disbursement
Revenue Receipts covers the tax revenues (like income tax, excise duty) and non-tax revenue (interest receipts, profits)
Capital Receipts holds money from market borrowings, recovery of loans etc.
Public Receipts act as medium for the flow of transaction, where government is merely acting as a banker (for instance: provident fund and small savings)
For a quick analysis of the aforementioned statements, ARIMA modelling is used to forecast for the upcoming two years (ie; 2018 and 2019).
ARIMA MODEL TO FORECAST THE ANNUAL FINANCIAL STATEMENT
Here is the synopsis of the CAPITAL ACCOUNT DISBURSEMENT using ARIMA:
The Capital Account Revenue statement is taken as the analysis sample:
The time series data is subjected to Augmented Dickey Fuller test for check the stationarity of the data
>x1<-log(CAR$AMOUNT) > adf.test(x1) Augmented Dickey-Fuller Test data: x1 Dickey-Fuller = -1.6901, Lag order = 2, p-value = 0.6904 alternative hypothesis: stationary
Since the data is not stationary, multiple differentiation is applied
>x2<-diff(x1) > adf.test(x2) Augmented Dickey-Fuller Test data: x2Dickey-Fuller = -1.9368, Lag order = 2, p-value = 0.5965 alternative hypothesis: stationary >x3<-diff(x2)> adf.test(x3) Augmented Dickey-Fuller Test data: x3Dickey-Fuller = -3.3127, Lag order = 2, p-value = 0.0899 alternative hypothesis: stationary > x4<-diff(x3)> adf.test(x4) Augmented Dickey-Fuller Test data: x4Dickey-Fuller = -5.214, Lag order = 2, p-value = 0.01 alternative hypothesis: stationary
The third difference gave a stationary data series
Auto Correlation Function and Partial Auto Correlation Function is employed to find out the order of the data series.
>acf(x1)
> pacf(x1) And the order of the data series is obtained as: AR=1, I=3, MA=0
> model1 <-arima(x1,order=c(1,3,0)) > summary(model1) Length Class Mode coef 1 -none- numeric sigma2 1 -none- numeric var.coef 1 -none- numeric mask 1 -none- logical loglik 1 -none- numeric aic 1 -none- numeric arma 7 -none- numeric residuals 23 ts numeric call 3 -none- call series 1 -none- character code 1 -none- numeric n.cond 1 -none- numeric nobs 1 -none- numeric model 10 -none- list > model1$coef ar1 -0.514188
And ARIMA model is employed to data and prediction function is used for forecasting for the years 2018 and 2019.
>pred1 <-predict(model1,2) > pred1 $pred Time Series: Start = 24 End = 25 Frequency = 1 [1] 16.03107 16.27264 $se Time Series: Start = 24 End = 25 Frequency = 1 [1] 0.3043931 0.8155953
And the forecasted values are plotted.
>x2<-c(x1,16.03107,16.27264) > x3<-cbind(x1,x2) >View(x3) > x3[24:25]<-NA >x4<-exp(x3) > plot(x4[,1],lwd=10,type="l",xlab="YEAR",ylab="AMOUNT") > lines(x4[,2],col="pink",lwd=3)
FORECASTED ANNUAL FINANCIAL STATEMENTS
$pred Time Series: Start = 24 End = 25 Frequency = 1 [1] 16.03107 16.27264 $se Time Series: Start = 24 End = 25 Frequency = 1 [1] 0.3043931 0.8155953
PUBLIC RECEIPTS REVENUE RECEIPTS
Particular | FORECASTED AMOUNT(IN CR) | |
2018 | 2019 | |
Capital Account Receipts | 9166536 | 11671260 |
Capital Account Disbursement | 9413355 | 12218601 |
Revenue Account Receipts | 10374796 | 12995712 |
Revenue Account Disbursement | 11475796 | 13996711 |
Public Account Receipts | 2419569 | 2708620 |
Public Account Disbursement | 2437077 | 2734721 |
KEY INSIGHTS FROM THE FORECAST
GST surveillance will incorporate more taxpayers under the same canopy which is significantly reflected in the uptick of forecasted Revenue Account Receipts for the years 2018 and 2019.
There is a chance of more disinvestment of public sector units, trailed by hike in borrowings and recoveries of NPA which in turn outlines in the Capital Account Receipts.
Proclivity to improve interest rates for provident fund, to lure more investment from the public, there is a increment in the Public Account Receipts which justifies the forecast.
This article is written by Anjali UJ and Shabin Nahab.
Good job.