College of Behavioral & Social Sciences
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Item LIVE and FIVE Estimation of Simultaneous Equations Models with Higher-Order Spatial and Social Interactions(2022) Chen, Jiankun; Prucha, Ingmar; Sweeting, Andrew; Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The first part of the dissertation introduces a new class of limited and full information GMM estimators for simultaneous equation systems (SEM) with network interdependence modeled by Cliff-Ord type spatial lags (Cliff and Ord (1973, 1981)). We consider the same model specification as that in Drukker, Egger, and Prucha (2022) and allow for higher order spatial lags in the dependent variables, the exogenous variables and the disturbances. The network is defined in terms of a measure of proximity and can accommodate a wide class of dependence structures that may appear in both micro and macro economic settings. We show that the scores of the log-likelihood function can be viewed as a weighted sum of linear and quadratic components that motivate valid moment conditions. One contribution of this dissertation is showing that the linear moments can be written to permit instrumental variable (IV) interpretation, extending on the existing results in the context of classical SEMs. Towards constructing the linear moments, the instruments exploit the nonlinear structure of the parameters implied by the reduced form model, while those utilized by the existing 2SLS- and 3SLS-type estimators do not. From this perspective, the new estimation methodology incorporates the ideas underlying the LIVE and the FIVE estimators in Brundy and Jorgenson (1971) for classical SEMs, as well as the IV estimators using optimal instruments for spatial autoregressive (SAR) models. In addition to the linear IV estimators, we also consider one-step GMM estimators that utilize both the linear and quadratic moments implied by the scores. Our new LIVE and FIVE estimators for the network SEMs remain computationally feasible even in large sample and are robust against heteroskedasticity of unknown form. Monte Carlo simulations show that the new estimators in general outperform the existing 2SLS- and 3SLS-type estimators for this class of models when the instruments are weak. In the second part of the dissertation, we estimate the consumer demand for gasoline in the market of Vancouver, Canada. We employ a demand system with a spatial network component, utilizing the model and the estimation methods considered in the first part. Demand elasticity for gasoline at aggregate level are well documented in the literature, while estimates at station level are relatively scarce. We estimate the station-level demand elasticities as well as (spatial) elasticity of substitution under a variety of network structures based on different proximity measures. We collected station-level data on retail prices, sales volume, station characteristics of the 151 stations, as well as the characteristics of local markets, for September 2019 as well as March 2020. To deal with the endogeneity of prices, existing works typically exploit variations in the characteristics of each station’s direct competitors. We argue that in a geographically continuous market, this strategy may not be sufficient. In spirit of Fan (2013), our instruments also exploit the variations in the characteristics of the competitors of each station’s competitors (indirect competitors). We find that the own-price demand elasticity is between −12 and −4 while the cross-station price elasticity is in general between 0.6 − 6, depending on the construction of the network matrices that governs the degree of competition. We also report the impact measures that provides interpretations on the estimated coefficients of the exogenous variables in the context of spatial network models. We find that the availability of service station in general have contributed positively on the sales volume at a station. In general, a station located within a neighborhood of more drivers face stronger demand.Item FOREST CHANGE AND OIL PALM EXPANSION IN INDONESIA: BIOPHYSICAL AND SOCIOECONOMIC ANALYSIS(2022) Xin, Yu; Sun, Laixiang; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Palm oil is the world's most widely used edible oil, and Indonesia has been the largest producer since 2007 and now makes up around 58% of the global market. The oil palm production has benefited the economic growth and lifted the living standards of local people in Indonesia, but this gain is often at the cost of replacing tropical forest, destructing peatland, inducing greenhouse gas (GHG) emissions, and reducing biodiversity. The expansion of oil palm plantation in Indonesia is bound to increase as the global demands continue to grow. The challenge of meeting the increased demand for oil palm products while effectively protecting tropical forest and its ecosystem services is an important tradeoff issue for both scientists and policymakers. However, little is known on the expansion patterns of oil palm in Indonesia, especially the underlying drivers with temporal and spatial details. To effectively address the knowledge gaps and deal with the challenges, this dissertation aims to first characterize the historical patterns driven by the variations in the benefits and costs of oil palm expansion across space and over time. It then projects the possible future spatial patterns and estimates the potential loss of land with high environmental values in order to meet the future global demand for oil palm products. This dissertation consists of three principle essays. The first essay identifies the major land sources of oil palm expansion in Indonesia with temporal details, and reveals the joint role of biophysical and socioeconomic drivers in shaping the spatial patterns of oil palm expansion by employing spatial panel models at the regency level. The second essay focuses on the temporal dynamics of the biophysical and socioeconomic drivers and the timing of estate crop (mainly oil palm) expansion by using Cox proportional hazard models (CPHMs) and their extensions with time-variant effects at the 1km × 1km grid level. It also explores the role of land use and land cover change (LCLUC) trajectory hopping in estate crop expansion into natural forest by introducing multi-state survival analysis to land-use science. The third essay projects the export demand for oil palm products from Indonesia by 2050 under different global trade scenarios with generalized geo-economic gravity models, and quantifies the possible tradeoffs between oil palm expansion and environmental conservation by allocating the projected demand to 1km × 1km grids across Indonesia applying parametric survival analysis. This study indicates that oil palm expansion in Indonesia has been strongly stimulated by the export value of oil palm products and prefers land with good biophysical suitability and infrastructure accessibility. As land resources become more limited, the effects of socioeconomic factors decrease following the ‘pecking order’ sequence, and the plantation expands into remote but fertile areas with high conversion costs or legal barriers. The degraded land surpassed natural forest and became the major direct land source of oil palm expansion in recent years, but degraded land had increasingly served as a land banking mechanism and a clearing-up tactic. This LCLUC trajectory hopping mechanism has made the protected area (PA) designations and sustainable development requirements become less and less effective in protecting tropical natural forest. Lowland secondary forest and peatland are the high-environmental-value (HEV) areas with the highest risks of conversion to oil palm plantation. To cope with the LCLUC trajectory hopping mechanism, Indonesia needs to have well-designed and fully enforced policies which limit/ban expansion into protected areas, peatland conversion, and deforestation of both primary and secondary forest. The country also needs more effective economic compensation mechanisms to promote more environment-friendly oil palm plantation. In this way, it is possible for Indonesia to maintain its leading position in oil palm production and exportation, while enhancing its role in environmental protection, such as climate change mitigation and biodiversity conservation. This dissertation improves our understanding of oil palm expansion in Indonesia by integrating economic science theory, advanced econometric techniques, and the best available remote-sensing data. It adds to the existing literature on analyzing the impacts of human behaviors on LCLUC at various spatial and temporal scales, especially from a longitudinal perspective.