Team Kenya

Outline Lessons learnt Case of Kenya: Overview Test for Stationarity of CPI variable VAR analysis Policy insights

1. Lessons Learnt How to test for stationarity using appropriate models, that is, testing for validity of including trend and/or constant term. Testing for stability / stationarity of a VAR model. How to use Eviews. How to interpret impulse response functions.

2. Case of Kenya: Overview Study period 2000:1 to 2013:3 Data source: Central Bank of Kenya and Kenya National Bureau of Statistics Frequency of data: Quarterly Variables: CPI, M3, RGDP, TB3, e, libor, oilprice Methodology: Granger causality, Johansen cointegration test, impulse response analysis

2. Test for Stationarity of CPI variable Step 1: View time graph of variable

2. Test for Stationarity of CPI variable Step 2: Conduct ADF test using trend and intercept F3 = 2.656 against CV = 6.50 Indicating that the trend term is not significant

2. Test for Stationarity of CPI variable Step 3: Conduct ADF test using intercept F3 = 0.033 against CV = 8.73 Indicating that the constant term is not significant

2. Test for Stationarity of CPI variable Step 4: Conduct ADF test without trend or intercept Conclusion: CPI is non stationary

2. Test for Stationarity of CPI variable Step 5: Conduct ADF test on DCPI Conclusion: CPI is I(1)

3. Estimate a VAR Step 1: Estimate unresticted VAR on log(rgdp) log(m3) tb3 log(e) log(cpi) and exogenous variables c libor log(oilprice) and 2 lags Step 2: Test lag length criteria Choose lag length of 1

3. Estimate a VAR Step 3: Estimate unresticted VAR on log(rgdp) log(m3) tb3 log(e) log(cpi) and exogenous variables c libor log(oilprice) and 1 lag Step 4: Test for VAR stability

3. Estimate a VAR

4. Analyse the VAR results Step 1: Estimate impulse response functions M3 has no impact on GDP. TB3 has negative impact on GDP four quarters after initial shock. Exchange rate has negative impact on GDP 5-6 quarters after the initial shock. M3 positively impacts on CPI after 5 quarters and persists thereafter. Interest rates and exchange rates have no significant impact on CPI.

4. Analyse the VAR results Step 2: Variance Decomposition After 10 quarters, 77.6% of variations in GDP is attributed to itself, 7.5% to exchange rate, 7.3% to CPI, 5.2% to interest rates and 2.5% to M3. After 10 quarters, 64.8% of variations in CPI is attributed to itself, 17.1% to GDP, 11.9% to M3, 4.5% to exchange rates and 1.5% to interest rates.

4. Analyse the VAR results Step 3: Granger Causality test M3 and CPI granger cause GDP, while TB3 and exchange rates do not cause granger GDP. M3 granger causes CPI.

4. Analyse the VAR results Step 4: Cointegration test Residual seems stationary, therefore, variables are cointegrated.

5. Policy insights Excessive money is not good for inflation in the medium-term. Raising short-term interest rates and depreciating the shilling will impact negatively on growth in the short term.

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