{'fraction_non_alphanumeric': 0.02072538860103627, 'fraction_numerical': 0.0019430051813471502, 'mean_word_length': 5.204819277108434, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Gravity Model Approach using Vector Autoregression in Indonesian Plywood Exports

This study aims to detect the determinants of plywood exports in Indonesia based on the Gravity model. Problems that occur are related to inefficient and effective exports. The analytical method uses Vector Autoregression with a single equation using a gravity model to analyze the factors that influence the flow of Indonesian plywood trade. The assumption results using Vector Autoregression (VAR), shows the results of the relationship between GDP, POP, ER, P, Dt and Vol with lag 1, this can be concluded that by observing the t-statistics of each coefficient, the reciprocal relationship between the variables GDP, POP, ER, P, Dt and Vol are statistically significant. Another variable besides the variable itself that has the most significant contribution to GDP is the distance t-1. The variable that has the most significant contribution to the population other than the population itself is Price (P) t-1. The variable that has the most significant contribution to ER besides the ER variable itself is Population. The variable that has the most significant contribution to Price (P) is the GDP variable. Other variables that have the most significant contribution to Distance (Dt) other than the Distance variable itself are variables of Indonesian Plywood Export Volume. Other variables that have the most significant contribution to Indonesia Plywood Export Volume in addition to the Indonesian Lapis Wood Export Volume variable itself are Population.