Elizabet Sri Rezeki, Gusmi Kholijah, Niken Rarasati

Laju Pertumbuhan Ekonomi Akibat Pandemi Covid-19 Di Provinsi Jambi Dengan Regresi Spasial

Introduction

Laju pertumbuhan ekonomi akibat pandemi covid-19 di provinsi jambi dengan regresi spasial. Analisis laju pertumbuhan ekonomi Provinsi Jambi di tengah pandemi Covid-19 menggunakan regresi spasial. Model SAR terbaik mengungkap penurunan ekonomi dan faktor-faktor signifikan.

Abstract

Dampak Pandemi Covid-19 bagi berbagai aspek kehidupan terutama bidang ekonomi sangat membuat perubahan pada berbagai sektor kehidupan, termasuk bidang ekonomi yang hampir mengalami resesi ekonomi. Pertumbuhan bidang ekonomi secara nasional mengalami penurunan hingga mempengaruhi ekonomi daerah di Indonesia. Kontraksi terhadap pertumbuhan ekonomi juga terjadi di Provinsi Jambi. Daerah ini mengalami penurunan ekonomi sebesar 0,99%. Disampaikan bahwa pertumbuhan bidang ekonomi antar daerah dapat saling mempengaruhi dengan daerah lain. Salah satu indikator yang digunakan untuk penilaian bidang ekonomi adalah pertumbuhan ekonomi. Adanya pengaruh efek wilayah antar lokasi dengan variabel dependen dapat menggunakan analisis regresi spasial. Karakteristik efek suatu wilayah berpengaruh dengan wilayah lainnya pada tiap kabupaten/kota dalam Provinsi Jambi perlu pada pertumbuhan ekonomi. Pertumbuhan ekonomi dapat dinilai dengan Produk Domestik Regional Bruto (PDRB) untuk setiap kabupaten/kota dapat dipengaruhi oleh jumlah kasus positif Covid-19 , jumlah fasilitas kesehatan yang menanggulangi pasien Covid-19Â , jumlah pelaku UMKM Â pendapatan per kapita di tiap kabupaten/kota , dan upah minimum kabupaten/kota . Pada penelitian diperoleh model regresi terbaik yaitu model Spatial Autoregressive (SAR) yang memiliki nilai koefisien determinasi sebesar 99,6877%. Hasil ini menunjukkan bahwa hanya satu variabel yang tidak signifikan yaitu jumlah fasilitas Kesehatan. Â Kata kunci: Covid-19, Laju Pertumbuhan Ekonomi, Spasial Autoregressive

Review

This paper presents a spatial regression analysis to investigate the impact of the Covid-19 pandemic on economic growth rates within Jambi Province, Indonesia. The study's focus on regional economic contraction and the potential for inter-regional economic influence, particularly during an unprecedented global health crisis, makes it a timely and relevant contribution. By employing spatial econometrics, the research aims to uncover how economic growth, measured by Gross Regional Domestic Product (GRDP), is affected by factors such as Covid-19 case numbers, health facilities, MSME activities, per capita income, and minimum wages across various municipalities/cities in Jambi. The methodological choice of spatial regression, specifically the Spatial Autoregressive (SAR) model, is well-justified given the explicit mention of inter-regional influences on economic growth. This approach is appropriate for capturing spatial dependence, a critical aspect often overlooked in standard regression analyses of regional data. The inclusion of a diverse set of explanatory variables, encompassing direct pandemic-related factors (Covid-19 cases, health facilities) and broader economic indicators (MSME, per capita income, UMK), provides a comprehensive framework for analysis. The abstract reports a remarkably high coefficient of determination (R-squared) of 99.6877%, suggesting an exceptionally strong explanatory power for the chosen model, and notes that only the number of health facilities was found to be statistically insignificant. While the study's focus and methodology are commendable, several aspects warrant further discussion and potential clarification. The exceptionally high R-squared value, while seemingly positive, is unusual for socio-economic and spatial data and might prompt questions regarding potential issues such as multicollinearity, data overfitting, or the nature of the variables included. A more in-depth interpretation of this result, perhaps alongside diagnostics for spatial autocorrelation and model stability, would strengthen the paper. Furthermore, a deeper exploration of why health facilities, intuitively linked to pandemic response, were found to be insignificant would add valuable nuance to the findings. Finally, the abstract could benefit from a clearer articulation of the study's practical implications and policy recommendations for Jambi Province based on the identified significant variables and the nature of the spatial dependencies.

Full Text

Comments

You need to be logged in to post a comment.