Three Essays on the Economic and Bioeconomic Dynamic Systems
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Three Essays on the Economic and Bioeconomic Dynamic Systems


Environmental and resource issues usually involve complex, dynamic, interconnected systems with feedback across social and environmental dimensions. My dissertation is a three-essay thesis exploring economic and bioeconomic dynamic systems. It utilizes a range of tools useful for tackling problems about environmental and resource management, including: analytical modeling, dynamic optimization, mathematical programming, and econometrics. The topics of each essay are:

modeling joint management of conflicting ecosystem services in the context of Lake Poyang commercial fishers' trip-level decision making about spatial location, fishing effort, and trip duration in the Gulf of Mexico longline fishery testing point identification of impulse response functions (IRF) using sign restrictions

Chapter 1 examines a coupled human-natural system characterizing the natural resource dynamics, human dynamics, and feedbacks between the two. The chapter develops a hydro-bio-economic model of ecosystem service management that illuminates the conflict between fishing operations and conservation of endangered and threatened waterfowl, specifically Siberian Cranes. The model is calibrated to fit the example of the China’s largest freshwater lake, Lake Poyang, the wintering ground for the last surviving population of Siberian Cranes. It captures important features of the lake's hydrology, ecosystem, and economics to investigate the impact of uncoordinated and coordinated management of fishing and bird conservation. The coordinated (joint) management problem is a three-state non-smooth hybrid dynamic problem that is within-year continuous and between-year discrete. It is solved using the novel pseudo-spectral method from aerospace engineering. The current regulations do not account for the externality fishing imposes on the endangered cranes, which results in their population size decreasing over time. In general, we find that prolonging the fishing season extends the cranes’ winter feeding and enhances survival but at a cost to the fishery. We characterize those trade-offs and then examine compensation schemes for fishery communities that induce crane conservation. With the decline in natural landscape quality, importance grows for utilizing working landscapes more effectively to provide ecosystem services.

Chapter 2 explores spatio-temporal human behavior using novel sources of high-resolution mobility data. With the advent of global positioning data in fisheries, now more than ever, we can empirically model fishers' decision-making at a detailed level. In the short-run, after choosing fishing gear, fishers decide where to fish, how much to fish in each location, and when to return to the port on a given trip. Most of the research investigating these decisions has focused on one aspect of the decision at a time (e.g., choosing a fishing location), treating other aspects exogenous or separable. However, these decisions are arguably interconnected and also conditional on the underlying vessel capital stock (e.g., hold and fuel capacity).

This chapter constructs a novel spatial dynamic model of an individual fisher's trip-level decision-making that incorporates simultaneous decisions on location choice, fishing effort allocated at each location, and travel route. It is motivated by observations from a high-resolution data set on fishing trips from the Gulf of Mexico's bottom longline fishery. We demonstrate predictions from the model using numerical simulations of calibrated optimal trip decisions. Simulation results show that technology constraints endogenously influence the trip length. These constraints impose a shadow price that affects the individual fisher's sequence of choices of location and effort from the outset of a trip. We compare these optimal spatial patterns with those from a myopic fisher and a partially myopic fisher, where the former makes one-choice-ahead decisions and the latter undertakes different degrees of forward-looking choices (2, 3, and 6 decisions ahead). The myopic fisher does not optimize route planning or consider the technological constraints until it is time to return to port. Both factors result in large reductions in trip profit even though, for example, catches can be similar across the myopic and dynamic fisher. For the partially myopic fisher, the extent of route planning and consideration of technological constraints depends on the degree of forward-lookingness. Not surprisingly, the more forward looking the partially myopic fisher, the closer it approaches the fully spatial-dynamically optimal trip pattern. Building more refined models of trip-level spatial decision making is important for the design and assessment of spatial and aspatial fishery management instruments.

Chapter 3 focuses on identifying impulse response function (IRF), the dynamic effect of a shock in a given moment along a specified time horizon, using sign restrictions. Sign restrictions on impulse response functions (IRF) are used to put bounds on parameters in structural vector autoregressions (SVAR) models. In this chapter, we provide testable necessary and sufficient conditions under which these bounds collapse to single point. The main necessary condition is positive linear dependence of the vectors of sign restricted IRF coefficients. We provide a simple test for this condition with standard chi-squared critical values that remain valid in the presence of redundant sign-restrictions. The simulations suggest that the proposed test has high power against the alternative data generating process with partial-identification.

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