xjl EXPY j ∑ ⋅ PRODY l Xj l
(5)
Where products are indexed by l, thus xj is the value of exports of product l for country j and Xj is the total of its exports. This report uses export data and aggregates from IMF Direction of Trade Statistics (DOTS) Online to calculate the year-on-year monthly percentage change of exports. The export data used to calculate EXPY indices are obtained from the United Nations Commodity Trade Statistics Database (COMTRADE) covering over 5000 products at the Harmonized System (1992) 6-digit level for the years 2004 to 2008. The value of exports is measured in current US dollars. The PRODY index for each 6-digit HS (1992) product is calculated as an average of PRODY from 2004-2006 generated from a consistent sample of 128 countries that reported trade in HS (1992) format in each of the years 2004, 2005 and 2006. The PRODY index was generated using data on GDP per capita in 2005 PPP-adjusted obtained from the World Development Indicators (WDI) Online. The average PRODY 2004-2006 is used to calculate EXPY of countries reporting export data in 2007. To generate the ratio of EXPY and GDP per capita, this report has used data on 2007 GDP per capita (2005 prices PPP-adjusted) obtained from the World Development Indicators (WDI) Online. Missing values and imputations All missing vales are assumed to be missing at random. We excluded all countries missing 30 per cent or more of data from the analysis, reducing the number of countries to 125. 11 ESCAP members’ were excluded this way in order to avoid over-imputation (Afghanistan, Brunei Darussalam, Turkmenistan, Kiribati, the Democratic People’s Republic of Korea, Marshall Islands, Federated States of Micronesia, Myanmar, Palau, Singapore, Timor-Leste). Another six countries (Eritrea, Guinea-Bissau, Haiti, Liberia and Zimbabwe) were excluded because imputation of missing values using past data for these countries failed to capture the impact of conflicts and social unrest in the period from 2000 until the present. We imputed missing values for the year 2007 for variables with available data from 2000-2006, by averaging values from the three most recent years for which data was available. Remaining missing values were imputed as follows. Missing values for EXPY were imputed using a method of multiple multivariate imputation of missing values (ice command in the Stata software package). This method uses switching regression, an iterative multivariable regression technique to impute the missing values. The method was applied using values for EXPY from 1962 to 2000 and 2004 to 2007, and values of GDP per capita in 2005 PPP-adjusted (2003 to 2007). The missing values of EXPY per GDP per capita were imputed using the imputed values of EXPY and actual values of GDP per capita in 2005 PPPadjusted (2007). Missing values for inbound tourism (as a percentage of GDP) were imputed using the method of multiple multivariate imputation of missing values and data related to the years 1990, 1995, 2000, 2003-2007 on international tourism receipt (as a percentage of GDP) and international tourist arrivals (thousand of people) (both series from UNWTO), and GDP (current) from WDI. Seven missing values for official development assistance data for countries that did not receive
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