Bian Yong. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2003. / Includes bibliographical references (leaves 34-37). / Abstracts in English and Chinese. / Chapter I. --- Introduction --- p.1 / Chapter II. --- Indeterminacy in a Small Open Economy Model with Endogenous Time Preference --- p.4 / Chapter 2.1 --- Economic Environment --- p.5 / Chapter 2.1.1 --- Technology --- p.5 / Chapter 2. 1. 2 --- Dynamic Model --- p.8 / Chapter 2.2 --- The indeterminacy result --- p.12 / Chapter 2.3 --- Conclusion --- p.12 / Chapter III. --- Indeterminacy in a Small Open Economy Model with Endogenous Labor Supply --- p.14 / Chapter 3. 1 --- Economic Environment --- p.17 / Chapter 3.2 --- Preference --- p.21 / Chapter 3.3 --- Dynamics of Equilibrium --- p.24 / Chapter 3.4 --- Indeterminacy and Scale Economies --- p.28 / Chapter 3. 4. 1 --- Case1 --- p.30 / Chapter 3.4.2 --- Case2 --- p.31 / Chapter 3.5 --- Conclusion --- p.32 / Chapter IV. --- References --- p.34 / Chapter V. --- Appendix --- p.38 / Chapter 5. 1 --- Technology --- p.38 / Chapter 5.2 --- Preference --- p.41 / Chapter 5. 3 --- Dynamics of Equilibrium --- p.43 / Chapter 5. 3. 1 --- Case1 --- p.49 / Chapter 5. 3. 2 --- Case2 --- p.50

Liquidity, often defined as the ability of markets to absorb large transactions without much effect on prices, plays a central role in the functioning of financial markets. This dissertation aims to investigate the implications of liquidity from several different perspectives, and can help to close the gap between theoretical modeling and practice. In the first part of the thesis, we study the implication of liquidity costs for systemic risks in markets cleared by multiple central counterparties (CCPs). Recent regulatory changes are trans- forming the multi-trillion dollar swaps market from a network of bilateral contracts to one in which swaps are cleared through central counterparties (CCPs). The stability of the new framework de- pends on the resilience of CCPs. Margin requirements are a CCP’s first line of defense against the default of a counterparty. To capture liquidity costs at default, margin requirements need to increase superlinearly in position size. However, convex margin requirements create an incentive for a swaps dealer to split its positions across multiple CCPs, effectively “hiding” potential liquidation costs from each CCP. To compensate, each CCP needs to set higher margin requirements than it would in isolation. In a model with two CCPs, we define an equilibrium as a pair of margin schedules through which both CCPs collect sufficient margin under a dealer’s optimal allocation of trades. In the case of linear price impact, we show that a necessary and sufficient condition for the existence of an equilibrium is that the two CCPs agree on liquidity costs, and we characterize all equilibria when this holds. A difference in views can lead to a race to the bottom. We provide extensions of this result and discuss its implications for CCP oversight and risk management. In the second part of the thesis, we provide a framework to estimate liquidity costs at a portfolio level. Traditionally, liquidity costs are estimated by means of single-asset models. Yet such an approach ignores the fact that, fundamentally, liquidity is a portfolio problem: asset prices are correlated. We develop a model to estimate portfolio liquidity costs through a multi-dimensional generalization of the optimal execution model of Almgren and Chriss (1999). Our model allows for the trading of standardized liquid bundles of assets (e.g., ETFs or indices). We show that the benefits of hedging when trading with many assets significantly reduce cost when liquidating a large position. In a “large-universe” asymptotic limit, where the correlations across a large number of assets arise from a relatively few underlying common factors, the liquidity cost of a portfolio is essentially driven by its idiosyncratic risk. Moreover, the additional benefit from trading standardized bundles is roughly equivalent to increasing the liquidity of individual assets. Our method is tractable and can be easily calibrated from market data. In the third part of the thesis, we look at liquidity from the perspective of market microstructure, we analyze the value of limit orders at different queue positions of the limit order book. Many modern financial markets are organized as electronic limit order books operating under a price- time priority rule. In such a setup, among all resting orders awaiting trade at a given price, earlier orders are prioritized for matching with contra-side liquidity takers. In practice, this creates a technological arms race among high-frequency traders and other automated market participants to establish early (and hence advantageous) positions in the resulting first-in-first-out (FIFO) queue. We develop a model for valuing orders based on their relative queue position. Our model identifies two important components of positional value. First, there is a static component that relates to the trade-off at an instant of trade execution between earning a spread and incurring adverse selection costs, and incorporates the fact that adverse selection costs are increasing with queue position. Second, there is also a dynamic component, that captures the optionality associated with the future value that accrues by locking in a given queue position. Our model offers predictions of order value at different positions in the queue as a function of market primitives, and can be empirically calibrated. We validate our model by comparing it with estimates of queue value realized in backtesting simulations using marker-by-order data, and find the predictions to be accurate. Moreover, for some large tick-size stocks, we find that queue value can be of the same order of magnitude as the bid-ask spread. This suggests that accurate valuation of queue position is a necessary and important ingredient in considering optimal execution or market-making strategies for such assets.

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This thesis consists of three self-contained chapters. Chapter I. The first chapter develops a dynamic general equilibrium model which includes financial intermediation and endogenous financial crises. Consistent with the data, financial crises occur out of prolonged (credit) boom periods and are initiated by a moderate adverse shock. The mechanism which gives rise to boom-bust episodes around financial crises is based on an interaction between the maturity mismatch of the financial sector and an agency problem which results in procyclical lending. I show how to model these features in a tractable way, giving a realistic representation of the financial sector's balance sheet and its lending behavior. The chapter provides empirical evidence on the behavior of the U.S. financial sector's market leverage which is (i) acyclical, (ii) rose mildly prior to the Great Recession, and (iii) increased sharply during the crisis; the model is consistent with these empirical facts. It also predicts and replicates the Great Recession, when confronted with a historical series of structural shocks. Finally, the framework is extended to include price rigidities, nominal debt contracts, and monetary policy. Within this version, I analyze the impact of monetary policy on financial stability and show that a U-shaped pattern of the policy target rate is most likely to increase financial instability. Chapter II. The second chapter models the economy as a time varying vector autoregression, consisting of economic and financial variables. The interest lies in the time varying response of these variables to a monetary policy shock. Monetary policy shocks are identified as the surprise component in policy announcements extracted from price changes in Federal Funds futures around such announcements. These monetary policy surprises enter the model as an exogenous variable. The framework is used to obtain evidence on the time varying response of stock prices to the monetary policy surprises. Stock prices always persistently decrease following a monetary tightening and more strongly than fundamentals imply - with an increase in risk-premia accounting for the difference. However, the response of stock prices varies over time. They decrease less during a boom and a perceived bubble period than during a recession. The findings suggest that so-called "leaning against the wind policies" may be ineffective since stock prices are less responsive during periods when such policies would disinflate asset bubbles using contractionary monetary policy. Chapter III. The third chapter augments a monetary dynamic general equilibrium model with a bubble as considered in [Miao_Wang_2015]. A bubble may exist in firms' stock market values and firms borrow against their inflated stock market values. Within this framework, I analyze the relation between monetary policy and the bubble. I find that contractionary monetary policy decreases the bubble which tightens borrowing constraints and amplifies the reaction of investment and output. These results are in contrast to the ones in Gali (2014) who considers a bubble of the classic rational type and finds that contractionary monetary policy can increase bubbles.

Office space oversupply cost Australia billions of dollars during the 1990-92 recession. Australia, the United States, Japan, the U.K., South Africa, China, Thailand, and many other countries have suffered office oversupply cycles. Illiquid untenanted office buildings impair investors capital and cash flows, with adverse effects on macroeconomics, financial institutions, and individuals. This study aims to develop improved methods for medium term forecasting of office market adjustments to inform individual project development decisions and thereby to mitigate office oversupply cycles. Methods combine qualitative research, econometric estimation, system dynamics simulation, and institutional economics. This research operationalises a problem solving research paradigm concept advocated by Ken Lusht. The research is also indebted to the late James Graaskamp, who was successful in linking industry and academic research through time and space specific feasibility studies to inform individual property development decisions. Qualitative research and literature provided a list of contributing causes of office oversupply including random shocks, faulty forecasting methods, fee driven deals, prisoners dilemma game, system dynamics (lags and adjustment times), land use regulation, and capital market issues. Rather than choosing among these, they are all considered to be causal to varying degrees. Moreover, there is synergy between combinations of these market imperfections. Office markets are complex evolving human designed systems (not time invariant) so each cycle has unique historical features. Data on Australian office markets were used to estimate office rent adjustment equations. Simulation models in spreadsheet and system dynamics software then integrate additional information with the statistical results to produce demand, supply, and rent forecasts. Results include ++ / models for rent forecasting and models for analysis related to policy and system redesign. The dissertation ends with two chapters on institutional reforms whereby better information might find application to improve market efficiency.Keywords. Office rents, rent adjustment, office market modelling, forecasting, system dynamics.

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Marine reserves have increasingly been recognised for their potential to address the pervasive problem of unsustainable harvest of fisheries worldwide. Biologists advocate the benefits of increased spawning biomass, larger modal sizes and greater densities of fish within marine reserves, and the possibility of spillover to adjacent fishable areas. Bioeconomic studies, however, find that pay-offs from stand-alone marine reserves rarely compete with sustainable yield management schemes, but that they can be beneficial when stocks are heavily exploited. Most of these bioeconomic models are analytical and deterministic in nature, and therefore ignore the redistribution of effort in response to closure and the inherent uncertainty of the marine environment. We present a bioeconomic analysis of a network of no-take areas around Stewart Island in New Zealand applied to the shellfish species paua (abalone) that incorporates both predicted redistribution and reduction in effort, as well as stochastic recruitment. A nested logit model is applied to spatially recorded catch and effort data by the Ministry of Fisheries between 1998 and 2003 to capture the two level decision-making process of divers. On any given day, divers decide whether to go diving at all, and if so, which of the 16 statistical areas around Stewart Island to visit. Weather conditions, spatially varying levels of catch per unit of effort and distance are used as explanatory variables to select areas for closure according to the �least economic impact� in terms of loss of diving trips. An age-structured biological model is developed with parameters specifically applied to paua stocks around Stewart Island. Virgin paua biomass as of 1974 is estimated on the basis of growth, survival, post-larval recruitment and egg production in the absence of fishing. Historic catch rates are then applied to find overall and area-specific levels of exploitation rates, spawning biomass, egg production, legal biomass and numbers of paua. In a final step, the economic model is linked to the biological model to simulate the imposition of no-take areas when taking account of the initial disproportional shift of harvest to fished areas in the first year, and the increase in overall pressure on legal biomass in the years thereafter. We contribute to the marine reserve debate by showing that in the very long run, the overall yield under closure of a relatively small area approaches and even slightly surpasses the yield under no closure for an assumed spillover gradient of 40% despite the redistribution of effort. The most important benefits of marine reserves emerge when stochastic recruitment is included in the recruitment function. In practice, predictions about the stock status and the impact of different harvest levels become much more difficult when acknowledging the inherent variability of the marine environment. The likelihood of stock collapse depends on the assumed value of two recruitment parameters, which highlights the effects of parameter uncertainty and emphasizes the role of marine reserves for population persistence. We also show that under uncertainty average yields under a management regime of a network of no-take areas in addition to the quota system can equal yields under no closure for an assumed spillover gradient of 40%, despite the increased pressure on areas adjacent to the closed areas. Our findings have significant implications for the management of the paua fishery at Stewart Island. For a heterogeneously abundant species, such as paua, spatial management in addition to quota limits could be vital in ensuring the long-term sustainability of the fishery given the inherent variability of the marine environment.