| Abstract: |
loyment in tourism and allied sectors of Indonesia; and to throw light on how
low-, medium, and high-skilled employment have been impacted during the
coronavirus disease(COVID-19) pandemic. We include both transport service
exports and travel service exports within the ambit of tourism exports.
Digitalisation is defined in terms of digitally deliverable services. The
study classifies employment at varying skill levels on the basis of
educational qualifications, and occupation-based skill classification is used
as a robustness check. The COVID-19 pandemic is captured with the help of a
time dummy variable and also using the Stringency Index. The study estimates
the bound testing approach to the autoregressive distributed lag (ARDL) model
using quarterly time series data, and the autoregressive moving average with
exogenous variable (ARMAX) model using monthly time series data, to understand
the nature of the long-run relationship and short-run dynamics amongst the
variables of interest. The study establishes the presence of cointegration
amongst employment, tourism exports, digitalisation, and other control
variables in all four cases – total employment, and low-, medium-, and
high-skilled employment. We find tourism exports to have a positive and
significant impact on employment, except high-skilled employment.
Digitalisation of tourism exports is found to have a significant but negative
impact on the total, low-skilled and medium skilled employment. The COVID-19
pandemic is also found to have a negative and significant impact on total
employment in Indonesia, with low-skilled employment being the worst affected. |