Abstract
Recent analysis regarding economic growth has started to accommodate growth interdependence. Spatial econometrics, which relies on the assumption of spatially autocorrelated economic growth, is the main tool of analysis. The spatial autocorrelation is commonly measured by Global Moran’s I, which is not robust to spatial outliers. The visualisation of available data indicates that East Java has experienced economic growth interdependence, but the Global Moran’s I for the GDP growth shows otherwise. The presence of spatial outliers is suspected as the cause of the insignificant spatial interaction. Using an average difference algorithm, this study detects the spatially outlying regencies/municipalities in terms of their yearly economic growth during 2011–2016. Based on the data, this study detects some spatially outlying regions, which mask the significance of the spatial interaction of the GDP growth among the regencies/ municipalities.
| Original language | English |
|---|---|
| Pages (from-to) | 1-14 |
| Number of pages | 14 |
| Journal | Regional Statistics |
| Volume | 11 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 2021 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 8 Decent Work and Economic Growth
Keywords
- average difference algorithm
- Global Moran’s I
- regional growth
- spatial outliers
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