**Table 13.**

*Exchange rate model: Financial flows only.*


If all BOP component included in the regression of Rupiah exchange rate model (**Table 15**), only financial account and crisis dummy that significantly affect rupiah

**Variable Coef. Prob** C 6.443 0.001 TB 0.000 0.247 FINANCIAL 0.000 0.060\* PRIMARY\_INCOME (2) 0.000 0.1715 LOG(M2) 0.187 0.126 DUMMY 0.103 0.018\*\* AR (1) 0.912 0.000\*\*\* Adj R2 0.952 Prob (F-stat) 0.000

*Contagion, Exchange Rate, and Financial Volatility: Indonesian Case in Global Financial…*

The empirical result shows the potential contagion from Argentina and Turkey's

Special thanks also go to the working group member of data dan input support,

Herry Gunawan, Ade Holis, Marhamah Muthoharoh, Muhammand Nalar, and Firdha Najiwa and to our research assistants Jonathan Aldo and Indria Nurhakim for

financial crisis to the Indonesian economy, especially to the stock market and exchange rate. The contagion from Argentina and Turkey in the stock market has been stronger than the exchange rate. The correlation between Indonesia's stock market with Turkey's is higher than the correlation with Argentina's stock market. Regression results also show that Indonesia's financial account, money, and commodity prices significantly affect exchange rates with different significance and magnitude. Regarding the exchange rate model, the Indonesian exchange rate, explained by the exchange rate of rupiah against the US dollar, has a strong positive association with the Turkish lira and Argentine peso exchange rate. The regression result also shows that Turkey has higher financial contagion effect than Argentina to Indonesian financial market. Indonesia and other emerging markets should be careful with the potential of financial contagion that has a probability to harm real sector activity. Policy anticipation to financial contagion should be taken as well as the structural fundamental policy to repair balance of payment and current account

exchange rate.

*Significant at α 0.1. \*\*Significant at α 0.05. \*\*\*Significant at α 0.01. Source: Authors, 2019.*

*\**

**Table 15.**

sustainability.

**59**

**Acknowledgements**

their data processing help.

**5. Conclusion and discussion**

*Exchange rate model: full BOP component.*

*DOI: http://dx.doi.org/10.5772/intechopen.92275*

#### **Table 14.**

*Exchange rate determination regression results: Full model with Argentina variables.*

rate has a positive association with rupiah exchange rate. If the peso depreciates to the dollar by one unit, the rupiah will depreciate too. The significance of Argentina peso is in 10% level of significance. Compared to lira regression in **Table 11**, the significance of lira is in 1% level of significance, which has the interpretation that Turkey has been proven to have larger potential effects to Indonesian financial sector than Argentina. In addition, the crisis dummy variables significantly influence the exchange rate with a positive direction, which means that crisis has caused rupiah to depreciate.

$$\begin{array}{l} \text{LOG}(\text{EXCH\\_RATE})\_t = a\_{10} + \beta\_{11} \text{TB}\_t + \beta\_{12} \text{FINANCE} \text{LA}\_t\\ \quad + \beta\_{13} \text{PRIAMY INCOMP}\_{t-2} + \beta\_{14} \text{LOG}(\text{M}\mathbf{2})\_t\\ \quad + \beta\_{15} \text{DUNMY}\_t + \beta\_{16} \text{AR}(\mathbf{1})\_t + \epsilon\_t \end{array} \tag{20}$$

*Contagion, Exchange Rate, and Financial Volatility: Indonesian Case in Global Financial… DOI: http://dx.doi.org/10.5772/intechopen.92275*


#### **Table 15.**

*Exchange rate model: full BOP component.*

If all BOP component included in the regression of Rupiah exchange rate model (**Table 15**), only financial account and crisis dummy that significantly affect rupiah exchange rate.

#### **5. Conclusion and discussion**

The empirical result shows the potential contagion from Argentina and Turkey's financial crisis to the Indonesian economy, especially to the stock market and exchange rate. The contagion from Argentina and Turkey in the stock market has been stronger than the exchange rate. The correlation between Indonesia's stock market with Turkey's is higher than the correlation with Argentina's stock market.

Regression results also show that Indonesia's financial account, money, and commodity prices significantly affect exchange rates with different significance and magnitude. Regarding the exchange rate model, the Indonesian exchange rate, explained by the exchange rate of rupiah against the US dollar, has a strong positive association with the Turkish lira and Argentine peso exchange rate. The regression result also shows that Turkey has higher financial contagion effect than Argentina to Indonesian financial market. Indonesia and other emerging markets should be careful with the potential of financial contagion that has a probability to harm real sector activity. Policy anticipation to financial contagion should be taken as well as the structural fundamental policy to repair balance of payment and current account sustainability.

#### **Acknowledgements**

Special thanks also go to the working group member of data dan input support, Herry Gunawan, Ade Holis, Marhamah Muthoharoh, Muhammand Nalar, and Firdha Najiwa and to our research assistants Jonathan Aldo and Indria Nurhakim for their data processing help.

rate has a positive association with rupiah exchange rate. If the peso depreciates to the dollar by one unit, the rupiah will depreciate too. The significance of Argentina peso is in 10% level of significance. Compared to lira regression in **Table 11**, the significance of lira is in 1% level of significance, which has the interpretation that Turkey has been proven to have larger potential effects to Indonesian financial sector than Argentina. In addition, the crisis dummy variables significantly influence the exchange rate with a positive direction, which means that crisis has caused

**Variable Coef. Prob** C 8.854 0.005 FINANCIAL �0.000 0.144 LOG(COMPRICE) �0.876 0.016\*\* LOG(M2) 0.298 0.062\* DUMMY 0.094 0.016\*\* AR (1) 0.946 0.000\*\*\* Adj R<sup>2</sup> 0.950 Prob (F-stat) 0.000

**Variable Coef. Prob** C 10,250,890 0.000 TB (�1) �0.049 0.149 FINANCIAL (�1) �0.019 0.072\* PRIMARY\_INCOME (�1) �0.077 0.286 ARS 5,932,025,000 0.081\* DUMMY 1,091,684,000 0.011\*\* AR (1) 0.923 0.000\*\*\* Adj R<sup>2</sup> 0.957 Prob (F-stat) 0.000

þ *β*13*PRIMARY INCOMEt*�<sup>2</sup> þ *β*14LOGð Þ *M*2 *<sup>t</sup>*

þ *β*15*DUMMYt* þ *β*16*AR*ð Þ1 *<sup>t</sup>* þ *ϵ<sup>t</sup>* (20)

*LOG EXCH* ð Þ \_*RATE <sup>t</sup>* ¼ *α*<sup>10</sup> þ *β*11*TBt* þ *β*12*FINANCIALt*

*Exchange rate determination regression results: Full model with Argentina variables.*

rupiah to depreciate.

*\**

*\**

**58**

**Table 14.**

*Significant at α 0.1. \*\*Significant at α 0.05. \*\*\*Significant at α 0.01. Source: Authors, 2019.*

**Table 13.**

*Significant at α 0.1. \*\*Significant at α 0.05. \*\*\*Significant at α 0.01. Source: Authors, 2019.*

*Exchange rate model: Financial flows only.*

*Public Sector Crisis Management*
