Penelitian ini mengkaji pengaruh liberalisasi perdagangan terhadap penurunan kemiskinan pada tingkat kabupaten/kota di Indonesia dalam kurun waktu 2000-2016 dengan menggunakan metode fixed effects. Regional tariff exposure digunakan untuk mengukur liberalisasi perdagangan pada tingkat kabupaten/kota yang dihitung dengan menggabungkan informasi mengenai struktur ekonomi pada masing-masing kabupaten/kota dengan tarif produk per sektor. Penelitian ini membedakan antara tarif output dan tarif input. Hasil pengukuran menunjukkan bahwa tarif output dan tarif input bervariasi menurut wilayah selama periode penelitian. Penelitian ini mencakup serangkaian metode fixed effects: fixed effects kabupaten/kota dan juga time-fixed effects yang mengontrol tren waktu agregat. Hasil penelitian menunjukkan bahwa dampak tarif output dan tarif input terhadap tingkat kemiskinan kabupaten/kota (P0) berbeda. Tarif output berkorelasi negatif dengan kemiskinan, sedangkan tarif input berkorelasi positif dengan kemiskinan. Hal ini menunjukkan bahwa liberalisasi perdagangan di sektor input dapat mengurangi kemiskinan di Indonesia. Penelitian ini juga menemukan bahwa PDRB per kapita, angka melek huruf, dan panjang jalan berasosiasi negatif dengan kemiskinan. Selain itu, dampak penurunan tarif input terhadap pengurangan kemiskinan akan lebih besar jika kabupaten/kota memiliki PDRB per kapita dan tingkat melek huruf yang lebih tinggi.
The study examines the effect of trade liberalization on poverty reduction across districts in Indonesia during the period from 2000 to 2016 using the fixed effect approach. Tariff exposure is used to measure trade liberalization, which is computed at district level by combining information on sector composition of the economy in each district and tariff lines by sectors. This study also distinguishes between tariff exposure for output products and intermediate inputs. This produces a measure indicating how changes in exposure to tariff reductions in outputs and inputs vary by region over the period. Due to the available multi-district and 17-year dataset, the study includes a set of fixed effects: the district-fixed effects, and also the time-fixed effects, which controls for aggregate time trend. The results indicate that the impact of output and input tariff on regional poverty headcount index (P0) is different. Output tariff has negative correlation with poverty while input tariff has positive correlation with poverty. This suggests that trade liberalization in input sectors could reduce poverty in Indonesia. It is also found that GRDP per capita, literacy rates, and road length are negatively associated with poverty. Also, the effect of reducing input tariffs on poverty reduction will be larger if the districts have higher GRDP per capita and higher literacy rates.
"Indonesia's population aged 60 years and over has doubled in the last two decades. Older adults will reach 19.9 percent in 2045, meaning almost one-fifth of Indonesia's population are elderly. Data Susenas 2021 showed that older people dominate the use of firewood and charcoal for cooking at about 18.72 percent, while the non-elderly population is only 10.29 percent. Using traditional cooking fuels like firewood and charcoal indicates energy poverty deprivation. Several studies have been conducted to investigate energy poor in older people and its impact on health, cognitive and mental health, and well-being with household unit analysis. Studies on the effect of multidimensional energy poverty (MEP) on older people's health with individuals are limited and have never been held in Indonesia. This study aims to measure MEP at the individual level of older people in Indonesia and then investigate its impact on their health status. This study uses the historical distance from each regency where the older people lived to the nearest power plant in 1985 as an instrumental variable to overcome the endogeneity problem. The Data processing results of Susenas from 2019 to 2021 found that the number of older people in Indonesia who experience multidimensional energy poverty (MEP) is still very high. There is 72,05 percent of older people who experience energy poverty in 2021. The result of OLS regression is that MEP significantly negatively correlates with older people's health. The coefficient from the two-stage least square estimation result, including all control variables, is -0.3964. At the mean level of the control group, multidimensional energy poverty reduces the health status of older people by 67,19 percent. This study further conducted western-eastern regional and urban-rural comparative analyses. The findings demonstrate that the health of older people in the eastern region is more severely affected, and multidimensional energy poverty deteriorates the health status of rural older people.
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