Consumers are not as rational as assumed by conventional economic theories. The present thesis reports three studies of consumers’ bounded rationality. It has three chapters. In Chapter 1, I investigate the effects of a range of different types of anchor on WTP and WTA valuations of familiar consumer products, elicited through individuals’ buying or selling decisions at given prices. I find anchoring effects only when the anchor value is framed as a plausible price for the good for which the individual is a potential buyer or seller. Anchoring effects are stronger for WTA than for WTP. I conclude that anchoring effects can affect market behaviour, but that not all anchors are equally effective. In Chapter 2, I demonstrate a set of three experiments and find that consumers are likely to stick to defaults and achieve suboptimal outcomes. I unpack two key psychological reasons why they do this - complexity (in terms of non-linearity, number and bundling of tariffs) and consumer inattention. The complexity induced by product bundling, non-linearity and number of tariffs has an important role, but this is overstated if the explanatory power of inattention is neglected. I show that a ‘smart nudge’ policy of automatically switching default tariffs can be used to exploit inattention-based consumer inertia to achieve better consumer outcomes. In Chapter 3, I report an experiment in which participants faced purchasing decisions involving complexity and common standards. The majority of participants employed the "dominance editing" (DE) heuristic. However, for cognitively constrained participants, the DE heuristic is less efficient than an alternative shortlisting heuristic - the "largest common standard" (LCS).

The most popular way environmental economists have quantified the worth we hold for wildlife has been through calculating a value for conservation or preservation practices. These typically focus upon endangered or charismatic species, and to an existence or non-use value which somebody holds for the creature in question. This thesis recognises that our value for wildlife may be more diverse than this. Indeed, it is highly feasible that people can derive an important yet cognitively disparate benefit from the animals and plants which they experience every day and which reside within close proximity to their homes. Using a combination of inter-disciplinary theories and techniques, this doctorate seeks to explore how mankind receives ‘nature connectivity’ value from local wildlife. This work implies that by undertaking a ‘warden-style’ role when interacting with the flora and fauna which resides upon our doorsteps, humans can satisfy a separate and distinct aspect of their subjective well-being from that which they establish through classic conservation mechanisms. Furthermore, this satisfaction may act as a substitute for other local social activities which are dwindling in modern UK society, including the participation in community or religious groups. The potential impact of these findings are that we may want to rethink the ways we approach the natural world if people are to maximise the participation in and welfare derived from their engagement with it. This includes attending to the behavioural and social infrastructure which can facilitate the opportunities for people to express and enjoy a connection with nature. More generally, the conjectures made here indicate the importance of understanding not only if values exist for environmental entities, but comprehending when these will be dampened or elevated. Until this can be done successfully, environmental economists will forever be fighting a losing battle to retain natural resources at socially optimum thresholds.

Occurrences of financial crises can be termed as 'legacy'. They have protracted history and each time occur with increasing vengeance and dangerous inflationary implications for the future. The problem lies deep in the structure of capitalist economies; both developed and developing. Despite their apparent variety however a common pattern regarding the occurrence of financial crises can be identified in major financial crises. This common pattern is exhibited in the cyclical deterioration of financial structures due to endogenous forces that lie mostly in the financial system. A state of tranquil economic activity (sustained economic activity) reigns for a considerable length of time before it is endogenously converted to investment boom (booming economic activity). Such an investment boom is then particularized in a single sector and is mostly financed by substandard credit. Myriad stimuli, mostly within the financial system, are at work during both of these stages, derailing the economy into unsustainable 'booming economic activity'. The economy, upon rupture of the credit bubble, experiences a big confidence shock, failure of financial institutions, credit freeze and/or debt deflation (burst of the bubble sector). Investigation of such cyclicality as a cause of recession is the core of this study. Endogenous forces in central banking that relate to monetary policy and in commercial banking that relate to supply and quality of credit make the economy behave cyclically. The scale and nature of any research problem however are proportionate to the methodology and effort that are required for its solution. Occurrence of financial crises is a large scale multidimensional problem i.e. monetary policy and its sub dimensions (interest rates, money quantity, inflation targets etc.) and commercial banking and its sub dimensions (level of agency, nature of their balance sheet) in the pre and post crises times. Quantitative models and secondary data research are powerful only under certain, albeit stringent, assumptions and - for research settings - dealing with simple linear problems. Keeping in view the nature and scale of the problem this study therefore employs questionnaire methodology to investigate the three-staged cyclicality and the instability role of central and commercial banking. Questionnaire findings are strengthened by semistructured interviews from fmancial institutions' personnel. Findings of the study support the three-staged cyclicality and the instability role of the financial system in such cyclicality. Remedial implications of the study are quite rich. The study provides consensus from the financial markets of the United Kingdom about the nature of credit crunches and instability. The solution of the financial crisis lies either in keeping the economy on the 'sustained economic activity' track or, if derailed into 'booming economic activity', aiding its retrieval into 'sustained economic activity' again. Dominant returns that are offered by a given sector due for example to some governmental relaxations result in unsustainable investment in that sector and thus in bubble formation. Rupture of the credit bubble affects the confidence of financial markets in the downward direction which results in speculation reversal causing large scale debt deflation. Government must therefore act to protect the financial system from such confidence shocks. It must act to protect the slumbering instability from awakening and therefore constantly vigil financial and non-financial sectoral prices, credits, and activity deviations. Similarly, commercial banks' risky behaviour can be contained by putting constraints on their sectoral operations.

Real-life decision-makers typically do not know all possible outcomes arising from alternative courses of action. Instead, when people face a problem, they may rely on the recollection of their past personal experience: the situation, the action taken, and the accompanying consequence. In addition, the applicability of a past experience in decision-making may depend on how similar the current problem is to situations encountered previously. Case-based decision theory (CBDT), proposed by Itzhak Gilboa and David Schmeidler (1995), formalises this type of analogical reasoning. While CBDT is intuitively appealing, only a few experimental and empirical studies have attempted to validate its predictions. This thesis reports two laboratory experiments and an empirical study that attempt to confirm the predictive power of CBDT vis-à-vis Bayesian reasoning.

This thesis aims to investigate the exchange rate behaviour and its abnormal movements. By doing so, I introduce a novel instrument which contributes to analyse the exchange rate behaviour. I then apply the new instrument, called wavelet analysis, to investigate the relation of exchange rate to price ratio (PPP proposition) and the relation of exchange rate and interest rates (UIRP proposition). Finally, I concentrate on the specific movements in exchange rate that leads to currency crises. The second chapter introduces wavelet analysis which has been extensively applied to many situations with favourable results. Many researchers are expanding wavelet application in a variety of fields such as signal processing, physics and astronomy. It has remarkable potential properties that can be applied in the disciplines of economics and financial. The first attempt of this chapter is to introduce wavelet analysis in an intuitive manner. The next step involves reviewing the potential and possible contributions of wavelet analysis in empirical economic and finance literature. I also examine the validity of short-run and long-run purchasing power parity (PPP) hypothesis applying wavelet analysis. The results indicate that the impact of price ratio on exchange rates are positive and close to unity. The findings confirm that the PPP holds for long-run horizon. The third chapter deals with examining the relationship between spot exchange rates and the interest rate differentials (UIRP) for ten bilateral currencies against the Pound Sterling in short and long time horizons, simultaneously. The distinguishing feature of this study is to apply wavelet transform to decompose the time series into short-run and long-run time horizons. I find out both negative and positive relationships between exchange rates and interest rate differentials. The former is supported by the fixed-price model in short-run and the latter is supported by flexible-price model in long-run. In the forth chapter, I evaluate the potential leading indicators of a currency crash by applying a quarterly panel of 26 developing and developed countries. I split the definition of currency crashes according to different generations of the currency crises in the literature. Based on two different definitions, I use two binomial logit models, which provide estimations of the probability of a currency crash occurring. The empirical results reveal that domestic credit growth rate, ratio of reserves to GDP, current account, output growth rate, and ratio of national debt to GDP are consistently associated with the early warning theory. According to definitions provided by this chapter, the findings show that current account and GDP growth rate in the developing countries and current account and national debt in the developed countries are significantly related to the crash incident. This chapter also criticizes the previous papers for their construction of exchange rate overvaluation indicator and proposes a recursive Kalman filter to express overvaluation. The findings confirm that overvaluation of exchange rate is not an appropriate predictor of currency crashes unlike previous studies.

Economic forecasting is important because it can affect the decision making processes of individuals, firms and governments so as to affect their behaviours. In this thesis, I discuss different methodologies for forecasting and forecast evaluation. I also discuss the role of assumption of normality and the role of uncertainty in economic forecasting. The first chapter is the introduction of the thesis. In second chapter, I conduct a Monte Carlo simulation to investigate the performances of forecast combination and the forecast encompassing test under the forecast errors non-normality. In third chapter, I examines the relationship between inflation forecast uncertainties and macroeconomic uncertainty for China by using different measures of uncertainties. I also investigate the relationship between inflation forecast uncertainties and inflation itself. In fourth chapter, I compute the probabilities of deflation for China by applying density forecast based on the theories and methodologies from previous two chapters. Particularly, I construct density forecasts for different forecast horizons by a joint distribution using Student-t copula. The fifth chapter is conclusion.

Instrumental Variable (IV) methods are widely used in the analysis of economic data when the explanatory variable of interest is endogenous and so OLS estimation of the model is biased. However, if the instruments used do not strongly predict the endogenous variable being instrumented then the IV estimator will also give biased results. Weak Instrument Asymptotic theory can be used to model the strength of the instruments in Two-Stage Least Squares (2SLS) IV models and critical values have been developed to test for Weak Instruments in models with one time period. In the first part of this thesis I extend Weak Instrument Asymptotics to a model with multiple endogenous variables where the instruments available can strongly predict each of the endogenous variables separately but correlation between the endogenous variables means that they cannot be jointly predicted and so the overall strength of the instruments in the model is weak. I develop a partial F-statistic to test for 'Weak Instruments of this form and show that this test has the correct size using currently existing critical values for testing for Weak Instruments. I then extend the Weak Instrument Asymptotics to Panel Data models with multiple time periods, and one endogenous variable. I show that it is no longer possible to use the F -statistic to test for Weak Instruments but it is possible to use the Effective F-statistic developed by Olea and Pflueger (2013) with appropriately clustered standard errors to test for 'Weak Instruments in Pallel Data models. Finally, I extend this analysis to look a AR(l) panel data models and show that it is possible to control the strcngth of the instruments asymptotically by changing the persistence of the autoregressive process. I also show the Effective F-statistic has the correct size in these AR(l) models.

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Players' use of cooperative strategies in Prisoner's Dilemma (PD) games and their achievement of coordination in some kinds of coordination games are among the most studied issues in both theoretical and experimental game theory. The present thesis is a collection of three article on this topic. Chapter 2 of the thesis focuses on cooperation, by developing an evolutionary model of a repeated Prisoner's Dilemma game, using replicator dynamics. The evolution of cooperation is analysed in terms of the interaction of different strategies, which represent the heterogeneity of forms of cooperation in civil life. One of the results of the paper is the conclusion that cooperation is favoured by heterogeneity: the presence of different kinds of strategies enhances cooperation. A theory that can explain both cooperation and coordination is team reasoning. Chapter 3 represents a development of Bacharach's theory of team reasoning. Starting from a detailed review of Bacharach's writings, and in order to clarify some issues linked to reasoning and frames, I propose a 'vacillation' model in which agents are allowed to have both I and we-concepts in their frames, and can easily switch from one to another. The theoretical model presented in Chapter 3 is followed by an experiment, reported in Chapter 4. The experiment aims at identifying which features of the structure of payoffs in coordination games favour the use of team reasoning, using Level-k theories as the benchmark for the modelling of individual reasoning. We find mixed evidence about level-k and team reasoning theories. In particular team reasoning theory fails to predict choices when it picks out a solution which is Pareto dominated and not compensated by greater equality. This could represent a step forward in investigating the roles of team reasoning and level-k reasoning in explaining coordinating behaviour.

This thesis explores the methodological and practical issues involved with synthesising the evidence required by economic decision models. Decision models represent a useful means of comparing alternative healthcare interventions in terms of their relative costs and effects. Cost-effectiveness estimates derived from these models along with the uncertainty around these estimates provide valuable information to guide decision makers when considering the implementation of interventions. Hence, care is required to ensure that these decisions are accurately represented by including all the relevant evidence in the model. This thesis demonstrates that decision modelling guidelines provide limited advice on how to synthesise evidence for the non-effectiveness parameters of a decision model. Furthermore, it is common to find a number of sources of evidence to inform these model parameters. Conversely, evidence may be unavailable or if it exists it may inform functions of these parameters rather than the individual model parameters. Hence, guidance is required on the best approaches to take account of these situations. Bayesian multi-parameter evidence synthesis (MPES) has recently been proposed as a method that can be used to synthesise evidence and address these issues. The thesis reviews the MPES, model fitting and evidence consistency methodologies. Two case studies are used to assess the value and generalisability of using MPES for decision analytic models; the focus is on the elicitation of expert opinion, meta-regression models and complex synthesis models. The advantages of MPES over traditional approaches for informing decision models are identified and discussed. The use of MPES methods for the purpose of decision modelling results in a valid and credible model, based on all available evidence, formally synthesised, systematically calibrated and checked for consistency and model fit. The thesis illustrates that these methods can be applied across very different disease areas. However, a caveat to their use is the time, resources and cross-discipline expertise required to build a MPES model as part of the economic evaluation. Interdisciplinary teams are a requirement to ensure the general adoption of these methods in health economics. Finally, it is recommended that MPES should be considered as one of the stages when developing a decision model.