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Jurnal Kebijakan Ekonomi

Abstract

The aims of this study was to examine the impact of implementation of the Large-Scale Social Restriction or PSBB policy on the concentration of particulate matter 2.5 (PM2.5). The observation period lasted from September 1, 2019 to December 31, 2020 in five major cities in Indonesia, namely Jakarta, Bandung, Yogyakarta, Semarang, and Surabaya. The data was processed using the fixed effect least square dummy variable (LSDV) model to test the impact of the PSBB policy or restrictions on citizen mobility to reduce the spread of COVID-19 on PM2.5 concentrations.

As a result, the PSBB policy had a very significant impact on the decline in PM2.5 to 1,210 μg/m3. When testing the impact of PSBB per level, of the 4 PSBB levels, PSBB level 3 significantly reduces PM2.5 concentrations. While PSBB level 1, PSBB level 2 and PSBB level 4 can have an impact on decreasing PM2.5 concentrations, but not significantly.

We hope this research can contribute to policy makers as a consideration when making decisions related to air quality control in Indonesia. Further research can be done by looking at the variable number of vehicles, the firmness of the apparatus in imple menting the PSBB.

Keyword: Air pollution, COVID-19, PM2.5, PSBB

Bahasa Abstract

Tujuan penelitian ini adalah untuk meneliti pengaruh polusi udara terhadap peningkatan kasus COVID-19 di Indonesia. Ada tiga polutan yang diuji dalam penelitian ini, yaitu: Particulate Matter 10 (PM10), Nitrogen Dioksida (NO2) dan Sulfur Dioksida (SO2). Periode pengamatan berlangsung selama 1 Maret 2020 sampai Desember 2020 di lima kota besar di Indonesia, yakni: Jakarta, Bandung, Yogyakarta, Semarang dan Surabaya. Di mana dalam periode tersebut ada masa penerapan Pembatasan Sosial Berskala Besar (PSBB) atau sejenisnya.

Penelitian ini menggunakan metode regresi data panel. Metode regresi panel data dipilih dengan harapan bisa mendapatkan hasil estimasi yang lebih presisi karena menggabungkan beberapa data periode waktu dan data individu. Tak heran jika saat ini kian banyak yang menggunakan metode regresi panel data untuk menganalisa sebuah kebijakan.

Dalam penelitian ini tahapan pengolahan data dimulai dengan membuat ringkasan diskriptif statistik. Selanjutnya dilakukan pemilihan model regresi dengan menggunakan metode Common Effect (CE), Fixed Effect (FE) dan Random Effect (RE). Setelah terpilih model regresi, dilanjutkan uji diagnostik, yang meliputi: uji multikoleniaritas, uji asumsi autokorelasi, uji heterokedastisitas, dan uji normalitas. Model regresi yang digunakan terjadi masalah autokorelasi, heteroskedastisitas dan normalitas. Sehingga kemudian digunakan metode Robust Standard Errors dalam regresi.

Hasil regresi dengan penerapan Robust Standard Errors menunjukkan bahwa PM10, SO2 dan NO2 memiliki pengaruh yang signifikan terhadap peningkatan kasus COVID-19 di lima kota di Indonesia; Jakarta, Bandung, Yogyakarta, Semarang dan Surabaya. Sementara untuk daerah lain masih perlu dilakukan kajian lebih mendalam lagi.

Kata Kunci: Air pollution, COVID-19, PM2.5, PSBB

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