Control variable ( )

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this chapter. The choice of the variables is determined by their availability in the dataset, adopted for this analysis and it is governed by relevance in terms of addressing key interests of the research questions which are based on theory and empirical review discussed in the section 3.2 above. The variables that are employed for the probability and intensity of CAL process analysis is in session 3.5 and their summary statistics are first presented in session 3.3.

3.3.1 Variable for modeling CAL events occurrences

In the empirical models discussed, the variables are divided into three main groups:

control variables, relevant independent variables: economic growth and financial instability measures and lastly, dependent variables: capital control measures.

3.3.1.1 Control variable ( )

In the estimation of Capital Account Liberalization estimation models, it is commonly recognized that independent control variables are classified into three categories:

macroeconomic, political and economic structure determinants of process. The selection of these independent control variables are guided by previous relevant research discussed in section 3.2 above, in order to answers the research questions.

Macroeconomic determinants

Past research has found that an expansion of current account deficits and changes in international interest rates are important for the changes in the Capital Account Liberalization Process (e.g. Eichengreen 2001, Glick Guo and Hutchison 2004, Milessi-Ferretti 1998, Bartolini and Drazen 1997b). They also found that an increase in the Capital Account Liberalization process intensity is positively related to the increase in current account deficits. On the other hand, a higher international interest rate is connected with the relaxation of capital control regulations, as the countries’ authorities are less likely to

xxt

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be worried about the risk of a speculative attack. However, Bartolini and Drazen (1997b) found a different correlation and suggested that, low world interest rates indicate small capital flows, meaning that there is no incentive to remove the regulation of capital controls.

Current account deficits are measured as, the current account as a percentage of the GDP (𝐶𝐴_!"/𝐺𝐷𝑃_!") in a country x at time t based on IMF’s International Financial Statistics database and on the World Development Indicators database. However, there is a significant difference with respect to data availability between these two databases. The World Development Indicators database provides a more complete dataset for this sample of countries over the period between 1995 and 2005.

The literature also finds two main methods for constructing the level of the real international interest rate (𝑟_!"^∗ ). Glick et al. (2006) and Roubini et al. (1984) constructed the level of the real international interest rate as a proxy of the level for the USA; real long-term interest rate (money market rate) is based on macroeconomic data series from IMF’s IFS. The real interest rate is the money market rate or alternatively, the discount rate for the year, minus the ex post CPI inflation rate over the past year, minus percentage change. Then, the other proxy, of the USA’s real long-term interest rate was considered as Government Bond Yield, corrected for inflation changes. Therefore, In order to obtain more a complete dataset, the first approach was employed in this analysis.

Thus, the level of the real international interest rate was calculated as:

1) The money market rate is IFS line 60 – Central Bank Policy rate;

2) The discount rate for the year minus the ex post CPI inflation rate over the past year is the difference between IFS line 60 b..zf– Federal funds rate and IFS line 64..xzf CPI%

change.

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Lastly, it is worth mentioning, that a relation between real domestic and internal interest rate, could be more important than the actual level of the international interest rate. If the international interest rate is equal to the domestic interest rate, there is no incentive for capital movements. In this case, the difference between interest rates is more important and will stimulate capital inflows and outflows. It is also possible that these variables are endogenous if current account deficits have changed or a world interest rate is adjusted in anticipation of liberalization of capital accounts and capital flows. This potential endogeneity issue was partially captured by lagging these macroeconomics factors by one year.

Further, analysis by Glick et al. (2005) and Alessandria and Qian (2005) indicated that, the positive effects of capital account liberalization are limited to countries with relatively well-developed financial systems, good accounting standards, strong creditor rights and the rule of law. Therefore, suggesting that countries, should reach a certain threshold in terms of institutional and economic development before they can expect to benefit from capital account liberalization. In order to investigate this effect, this paper followed the works of Demirguc-Kunt and Levine (2001) and used the private-credit/GDP ratio as an indicator of financial development as drawn from the IMF IFS.¹

Following Roubini and Sala-i-Martin (1992), financial repression was adopted and is defined as a discrete variable that takes the value 1 when the average of the real interest rate is over the current rate and also for the previous four years this rate was positive, 2 when this rate is negative but higher than 5%, and 3 when it is lower than 5%. The real interest rate is defined as the money market rate or, alternatively, the discount rate for the year, minus the ex post CPI inflation rate over the past year (IFS line 60 or 60b minus the percentage change in line 64). Apart from these measures of financial development, all variables are presented in Table 3.1.

1 The private-credit/GDP ratio is defined as line 32d divided by line 99b, the financial development variables were implemented into estimation, but there were not statistical significant as the results of this, they were not included in Table 3.1.

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Economic structure variables

The other control independent variables that are essential to this empirical analysis are presented here in the literature, Glick et al. (2004), Milessi-Ferretti (1998) and Grilli et al.

(1995) found that there is a positive correlation between the increase in the intensity of the capital liberalization process and the relaxation of fiscal policy and trade openness.

Furthermore, Bai and Wei (2000) and Milessi-Ferretti (1998) also established that countries with more independent central banks were less likely to use controls, and by the same token, country-individual characteristics include two economic structure variables such as, trade openness (𝑂𝑃_𝒙𝒕) and “monetary freedom” index (𝑀𝐹_𝒙𝒕) for country x at time t.

In order to obtain precise a measure for trade openness and relaxation of fiscal policy, the approach adopted here, follows Glick et al. (2004). The openness to world trade (𝑂𝑃_!") is measured by the sum of export and import as a percentage of the GDP and this index was taken from the IMF IFS CD-ROM. A relaxation of fiscal policy (𝐺_!"/𝐺𝐷𝑃_!") is computed as the relative size of government spending as a percentage of the GDP at market price. This variable was constructed based on information from the United National Common Database and World Development Indicators.

The other economic structure variable, the “monetary freedom” index (𝑀𝐹_𝒙𝒕) was taken from the Economic Freedom index, from the Heritage Foundation for the period 1995-2012. The range of the “monetary freedom” index (𝑀𝐹_𝒙𝒕) is between 0-100 percent, higher the value of the index; it indicates a more independent monetary policy in the country.

Political explanatory variable

In the literature, Rodrik (1998), Edison et al. (2004) and Klein (2003) pointed out that capital account openness might be intensely impacted by the quality of the government and other political institutional variables. Therefore, a political explanatory variable (𝑃𝐹_!") was incorporated from the Economic Freedom index, from the Heritage Foundation for

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the period 1995-2012 as the following: a continuous variable has a range between ‘0’ and

‘3’, where ‘0’ indicates highest level of political freedom, and ‘3’ is full political control.

This variable also captures the policy of influence on capital control, in other words political stability is associated with a lower rate of capital control regulation (Eichengreen 2001, Glick, Guo and Hutchison 2005 and Grilli and Milessi-Ferretti 1995).