Notwithstanding the proven achievements of the New-Keynesian research programme, the models currently used for monetary policy analysis rely on two assumptions that are often taken for granted. One is the balanced growth path property, which has generally been an accurate description of the US and other advanced economies. The other assumption concerns the small volatility of shocks that enables the researcher to approximate the solution of the original model locally. In the past decade, however, emerging economies such as China, Brazil, the Czech Republic or Poland have experienced persistent growth rates of GDP per capita that have been well above the corresponding levels in the euro area or the US. But how should monetary policy respond to an ongoing real convergence process which precisely differentiates emerging from advanced economies? The first part of the thesis aims to answer this question in the context of economies also bound to become future members of the euro area. Owing to the long-term institutional commitment to satisfy the Maastricht convergence criteria during the ERM-II mechanism, policy makers in Central Europe face the additional responsibility of managing the tension between nominal and real convergence. For instance, the Balassa-Samuelson hypothesis postulates an empirically relevant reason as to why countries engaged in a catching-up process might experience a higher inflation rate brought about by the increase in the relative price of services. Motivated by the stylised facts of macroeconomic dynamics in the Czech Republic, a country we take as representative for the whole region, Chapter 1 develops a stylised SOE model with nominal rigidities that is subject to asymmetric productivity growth shocks affecting the traded and nontraded sectors. Relative to the existing literature analysing optimal monetary policy under commitment in Balassa-Samuelson type of macroeconomic environments, the model we propose differentiates itself in that it allows for endogenous current account fluctuations and uncorrected steady state distortions. These modifications result in richer dynamics, which are shaped by the possibility to influence the terms of trade in one’s favour and the presence of monopoly power in product markets. In setting up the welfare maximising interest rate responses, the optimal plan trades off conflicting inflationary and deflationary incentives stemming from the existence of the above externalities. Whereas the first chapter focuses on the methods and assumptions needed to detrend the nonstationary model, the second chapter examines the optimal monetary policy stance under real convergence in two different market structures. The simulations reveal that the specific policy recommendations depend on the degree of substitutability between domestic and foreign goods, a parameter which also alters the strength of the wealth effects driving consumption responses. When monopolistic competition in the traded sector is assumed, the Ramsey interest rate plan is countercyclical. Owing to a cancellation of the terms of trade externality, the predictions are however reversed under perfect competition. This is because the incentive to stimulate production away from the inefficient steady state level becomes dominant. Additionally, the study conducts an extensive welfare analysis through which the effectiveness of inflation targeting and exchange rate peg regimes is assessed relative to the Ramsey plan. It is shown that policies achieving appropriate measures of price stability robustly deliver higher conditional welfare during a catching-up process. The analysis is suggestively complemented with policy experiments that are relevant to the ERM-II period, such as the Maastricht constrained optimal plan, its welfare costs and the welfare-maximising choice of a central parity at which the nominal exchange rate should be fixed. The final part of the thesis examines the macroeconomic costs of euro adoption in Emerging Europe, conditional on the EMU membership eventuality. Inspired from the Optimum Currency Areas literature, the research conducted in the third chapter investigates the circumstances when the decisions made by the ECB would correspond to the domestic optimal interest rate responses. The empirical work looks at the structural alignment and the degree of business cycle synchronisation between prospective and current members of the single currency area, modelled suggestively as the Czech and Austrian economies. A rich SOE model with incomplete markets and trade in intermediate inputs is developed in this sense, whose core structure is similar to Kollmann (2001). Relative to the original framework, we augment its shock structure and enrich the dynamics by incorporating external habit formation and partial indexation in the Calvo adjustment rules for prices and wages. The state-space representation of the DSGE model is taken to data and the set of random parameters is estimated using Bayesian techniques. The comparative analysis reveals that most structural parameters are not very far from each other, suggesting that a moderate degree of structural convergence has been achieved by the emerging economy. The costs of losing monetary policy sovereignty are further assessed by employing a battery of tests, which include impulse response analyses and historical decompositions of output and inflation. While confirming previous SVAR evidence, the results suggest that the propagation mechanisms of monetary policy, productivity and demand shocks are remarkably similar across the two economies. In contrast, the analysis also indicates considerable asymmetries of the sources of fluctuations, which were more volatile and largely idiosyncratic in the Czech Republic. The low degree of business cycle synchronisation suggests that coping with euro area interest rates on a permanent basis is likely to be painful.

This thesis explores the role of trade and trade liberalization policies on Tanzanian economy with special focus on the performance of agricultural sector. In terms of methodology, we first use parametric and non-parametric tests to evaluate the impact of liberalization policies on the growth rate of exports. Secondly, we use ordinary least square and instrumental variable to test the “inverse relationship hypothesis” and then we estimate the effect of liberalization on land productivity. We also extend this analysis to Uganda in order to ascertain whether similar findings could be replicated in other developing countries. Thirdly, we employ the co-integration technique to evaluate the effects of openness on economic growth. The parametric and non-parametric tests shows that: despite the marked variation in the composition of traditional exports especially during the late 1990s; largely from coffee and cotton to cashewnuts and tobacco, the contribution of trade liberalization in fostering export growth is rather weak. Second, although the volume of food crops during the post reform period is much higher than before the reforms, there are no symptoms of increased growth overtime. The empirical evidence from econometric analysis shows the existence of diminishing returns to land in the agricultural sector. On the other hand, the impact of trade liberalization on land productivity is mixed; while in some traditional exports its impact is negative and significant, in others the impact is positive but not significant. Contrary to the conventional wisdom as documented in the traditional theories of comparative advantage, the problem with Tanzanian agriculture is not related to the land size but low productivity. Interestingly, these results are also replicated in the Ugandan case. The cointegration analysis shows that the share of trade to GDP is negatively correlated with economic growth. In general, the contribution of this thesis has wider implications in the development policy, at least for the case of Tanzania and other developing countries. First, trade liberalization policies are counterproductive unless diminishing returns to land is squarely addressed. Secondly, the existence of diminishing returns to land is incompatible with the simple prediction of the theory of comparative advantage. The presumption behind trade liberalization is that specialization according to the “comparative advantage” doctrine would inevitably enhance increased productivity (i.e., efficiency). Our results do not conform to this presumption. Third, diminishing returns means that as production increases with international specialization, every additional unit of commodity produced would be more expensive to produce. Fourth, the persistence of diminishing returns to land is incompatible with poverty reduction.

This thesis investigates the monetary transmission mechanism in the Euro area, for countries taken individually and as an aggregate. The focus of the thesis is on the effects of monetary policy shocks on the area as a whole, across countries and over time during the period of single monetary policy by the Eurosystem. Using the mostrecent empirical techniques such as factor-augmented vector autoregression (VAR), Bayesian Gibbs sampling, rolling windows, data pre-screening and panel VAR, the thesis investigates a novel (large) data set for the economies of the Euro area. According to our empirical analyses utilising these techniques, the thesis reaches the following main conclusions: First, time variation in the impulse responses of area-wide consumer prices and monetary aggregates to monetary policy shocks is stronger than that of other key macroeconomic indicators. The contractionary impact of the monetary tightening on real activity is the strongest when it hits the economy during the global financial crisis period (Chapter 1). Second, although the effects of the policy shocks on national real activities and price levels are homogeneous across countries, the transmission mechanism displays important cross-country heterogeneity with the national monetary aggregates responding most heterogeneously to common monetary policy shocks (Chapter 2). Finally, despite the responses of the Eurosystem to the global financial crisis with unconventional monetary measures, country-specific factors such as defaults risks and bailouts played a significant role in disrupting the transmission of the policy actions to individual economic activities (Chapter 3).

Chapter 1: We propose an integral correction mechanism to model real exchange rate dynamics. In estimation, we also allow a Harrod-Balassa-Samuelson effect on real exchange rate long-run equilibrium. Using data from 19 OECD countries, we find the integral correction mechanism fitting in-sample data significantly better than the popular smooth transition autoregression model. The special dynamics of the integral correction mechanism help explain the PPP puzzle by distinguishing mean-reversion speeds in the long- and short- run. However, the integral correction mechanism shows a significant out-of-sample forecast gain over the random walk in only few cases. Though the gain is robust across forecast horizons and quite large at long horizons. Chapter 2: This chapter evaluates the ability of a standard IRBC model augmented with an input adjustment cost of imported goods to explain different aspects of the real exchange rate like the standard deviation, the autocorrelation function, the spectrum and the integral correction mechanism. I find that the simple IRBC model with an appropriate calibration can well capture all features of the real exchange rate. The input adjustment cost plays the key role. As compared to the standard model, it implies a reversed impulse response of the real exchange rate with a fast speed going back to steady state and introduces a long-run cyclical movement in most macroeconomic variables. I find that this particular impulse response helps explain the PPP puzzle. Chapter 3: I study optimal unconventional monetary policy under commitment in a two-country model where domestic policy entails larger spillovers to foreign countries. Equity injections into financial intermediaries turn out to be more efficient than discount window lending and the large-scale asset purchases that have been employed in many countries. Due to precautionary effects of future crises, a central bank should exit from its policy more slowly than the speed of deleveraging in the financial sector. The optimal policy can be changed considerably if cross-country policy cooperation is not imposed. In this case, interventions tend to be too strong in one country but too weak in the other. Gains from cooperation become positive if using unconventional monetary policy is costly enough, then correlates positively with the cost. Chapter 4: I consider the implementation of optimal unconventional monetary policy outlined in chapter 3. I find the Ramsey policy characterised by a simple rules responding to gaps in asset prices. However, it requires knowledge of asset prices that would be realized in a world free of financial friction so cannot be used to guide unconventional monetary policy in practice. The best practical simple rule responds to credit spread with inertia.

This thesis is an application of Random Matrix Theory (RMT) to portfolio management and financial networks. From a portfolio management perspective, we apply the RMT approach to clean measurement noise from correlation matrices constructed for large portfolios of stocks of the FTSE 100. We apply this methodology to a number of correlation estimators, i.e., the sample correlation matrix, the Constant Conditional Correlation Model (CCC) of Bollerslev (1990), the Dynamic Conditional Correlation (DCC) Model of Engle (2002) and the Regime-Switching Beta CAPM Correlation Model, based on Ang and Bekaert (2004). For these estimators, we find that the RMT- filtering delivers portfolios with the lowest realised risk, the best prediction accuracy and also the highest cumulated returns and Sharpe Ratios. The gains from using the RMT-filtering, in terms of cumulated wealth, range from 65%, for the sample correlation matrix to 30%, for the regime-dependent correlation estimator. In the case of regime switching CAPM models, we find that the regime switching correlation matrices, in the high volatility regime are found to be a good filter which makes further RMT- filtering to be redundant. This establishes the validity of using regime sensitive portfolio management to deal with asymmetric asset correlations during high and low volatility regimes. From a financial network perspective, we assess the stability of a global banking network built from bilateral exposures of 18 BIS reporting banking systems to net debtor countries. For this, we applied the eigen-pair method of Markose (2012), which is based on the work of May (1972, 1974) for random networks. We use a stability condition based on the maximum eigenvalue (λmax) of a matrix of net bilateral exposures relative to equity capital as a systemic risk index (SRI). We provide evidence of the early warning capabilities of λmax, when this surpasses a prespecified threshold. We use the right and left associated eigenvectors as a gauge for systemic importance and systemic vulnerability, respectively. The λmax SRI was found to be superior in terms of early warning when compared to the standard SRIs based on market price data, viz. the DCC-MES of Acharya et al. (2010), the SRISK of Acharya et al. (2012) and the DCC-ΔCoVaR of Adrian and Brunnermeier (2011).

This thesis examines how bank market structure affects industry performance in developing countries. A high degree of bank concentration would be associated with tight constraints and high borrowing costs, while it has also been argued that, it would be easier for firms to access credit if the banking system is concentrated. Foreign banks are seen to promote financial development and spur economic growth; while critics suggest that a larger foreign bank presence in developing countries is associated with less credit to the private sector. Also, government ownership of banks is responsible lower economic and slow financial development, while others argue that government banks promote long-run growth. The implications of bank market structure on the real economy are examined using cross-country, cross-industry panel data from developing countries, along with a variety of econometric techniques, and standard measures of industry performance. The research aims to ascertain whether bank market structure in developing countries influences financing for firms differently as a result of industry-specific characteristics. It also examines if institutional characteristics helps in explaining industrial performance in the short-run. As a follow-up to one of the findings, the research examines if banks would prefer to fund innovative firms in a liberalized environment by exploring the impact of financial development on the export structure. The main empirical findings are as follows: first, it may not be possible to identify robust or consistent findings concerning the effects of good institutions; secondly, it might not necessarily be the case that financial development specifically benefits firms based on specific industry characteristics; and finally, the research finds that banking sector development reduces export sophistication and increases export concentration. This may suggest that banking sector development enforces specialization according to existing comparative advantage.

Various models explaining micro knowledge-generating behaviour (in particular exporting and innovating) in the economics literature are underpinned by the overlapping assumption that these activities are largely determined by the resources/capabilities possessed by firms. Despite their perceived importance, there is a dearth of evidence on how these heterogeneous resources and firm-specific capabilities can be incorporated into economics models to quantify their roles in determining microeconomic behaviour. Therefore this thesis attempts to bridge this gap in the literature by integrating the resource-based view (RBV) as a new IO theory into the microeconomics literature and empirically utilising micro level data to investigate the significance of such resources/capacities in determining exporting and innovation activities, moderating their inter-relationships as well as conditioning their impacts on the firm’s performance. These heterogeneous resources have been proxied using firm size, productivity, capital intensity, intangible assets, various dimensions to absorptive capacity, the deployment of R&D sourcing strategies and so on. Using establishment-level data covering all UK market-based sectors in 2000, the findings show that all these factors have a large impact upon the propensity and/or intensity of establishments’ exporting and/or R&D activities, with an especially noticeable role in breaking down entry barriers to undertaking such activities. Given the significant impact of exports on knowledge-creating R&D activity, the thesis subsequently investigates and confirms additional learning effect of exporting as embodied in the firm-level exports-productivity relationship using a nationally representative panel dataset covering both manufacturing and services sectors in the UK, for the 1996-2004 period. Lastly, this thesis also attempts to provide an initial inspection of the contribution of innovation (proxied by R&D stock) to productivity using plant-level panel data for Northern Ireland. Based on the estimation of a ‘knowledge production function’ separately for various manufacturing industries, the overall long-run results show that R&D stock does have a positive impact upon productivity.

This thesis makes use of recently collected UK Community Innovation Survey data to investigate 3 areas that allow to characterise and thus understand more clearly the innovation process in the UK. Firstly strategies of innovation used by firms are identified. Next the determinants of innovation, that is factors driving innovation inputs and outputs, are estimated. Thirdly this work examines the effectiveness of financial public support towards innovation. This also allows to establish which firms are more likely to be in receipt of public support and thus whether government innovation policy is in line with its objectives. Furthermore in this thesis a measure of absorptive capacity for the CIS is created, to see whether this proxy contributes in explaining innovative activities and the receipt of public support towards innovation. Similarly a measure of appropriability is generated for use as an explanatory variable in the estimation of the determinants of innovation. Both of these measures permit to find out if their latent variables have nonlinear effects in explaining propensity and extent of innovative spending. All these aspects have not received attention in previous literature, in large part due to the novelty of the data used. Besides the empirical evidence gained on the above, the addition to the literature of this thesis lies in examining several CIS survey rounds together. For one this serves as a robustness check for the conducted applications and on the other hand it allows investigating the comparability of the survey rounds. For this work the CIS 4, the CIS 5 and the CIS 6 are used as they are the most similar and comparable samples of UK businesses to date. Nevertheless it was found that differences in terms of design, wording and exclusion of responses to some question sets in the different surveys impedes their use for trend analysis and panel data analysis. Something the data collecting agencies need to address in the future. Despite these issues the conducted investigation has provided useful insights into innovation as it takes place in the UK. The first empirical chapter has been able to identify two major modes of innovation as captured by the survey. A ‘traditional’ or ‘linear’ strategy aimed at introducing product and process innovations, relying on innovative activities such as R&D and also making use of sources of information, more strongly from market sources then from science sources. Secondly a ‘dynamic’ or ‘systemic’ strategy also involving innovative activities such as R&D but more strongly making use of knowledge sources from science as well as relying on cooperation. The interpretation of this “blue skies strategy” which is not directly linked to achieving technological outputs is that it generates knowledge that helps to keep abreast of market developments and to be ready to spot opportunities in line with the literature on dynamic capabilities thus the identified strategies allow for a plausible interpretation congruent with innovation theory. In this chapter the aforementioned measure of appropriation and absorptive capacity were also successfully generated. These were then shown to play a significant role in explaining innovative activities in the subsequent empirical chapter, both exhibiting decreasing returns to scale. Following the CDM methodology this work has confirmed that knowledge capital as proxied by predicted R&D spending intensity is as important in generating service innovations as it is in stimulating goods innovations for the UK. The results also show that absorptive capacity not only indirectly impacts the likehood of introducing service innovations through its effect on knowledge capital as for goods innovations but also directly. This suggests that services once conceived further have to be tailored to individual customer’s needs. Hence absorptive capacity is specifically important in a developed economy dominated by service sector industries. At the same time the fit of the models confirmed that the CIS could do better at explaining service and process innovations by soliciting more information that are likely to cause these types of innovation. Finally further support for the innovation productivity nexus has been found. The last empirical chapter then established that absorptive capacity is also an important factor explaining the likehood of firms to be in receipt of financial public support towards innovation. This chapter further concluded that the financial public support towards innovation in the UK has in the recent past been effective at stimulating innovative performance besides just R&D spending. The government’s objective of supporting start-ups, that potentially face difficulties in financing their innovative activities, as well as supporting cooperation, vital for the dissemination of knowledge in the economy, is met according to the results. However SMEs could not be shown to be statistically more likely to be in receipt of public support despite facing the same problems as start-ups, though at least they are not less likely to be in receipt of public support then large firms. This finding stipulates that policy objectives are not achieved with regard to specifically targeting SMEs.

The 16 publications included in this thesis are the results of a programme of research between 1993 and 2009 into the labour market and labour market-related impacts of the large-scale spatially concentrated losses of industrial jobs in Great Britain from the 1970s to the 1990s. The British conventional wisdom has been that labour market recovery was relatively quick, and that the effects were not particularly profound. Continuing labour market distress was mainly ascribed to labour ‘supply-side’ factors rather than to locally deficient labour demand. The research challenges these views. It draws particularly on the British Keynesian tradition, and on authors such as J. F. Kain, John Kasarda and William Julius Wilson from the USA, which experienced similar job losses around a decade earlier. Issues covered include the statistical measurement and spatial variation of unemployment and related economic disadvantage, unemployment disguised as sickness, long-term unemployment, migration and lone parenthood, and there is also analysis of policies on employment and social inclusion. The research shows that ‘Travel-to-Work Areas’ (TTWAs) do not correctly identify the employment ‘fields’ of residents of areas of high unemployment. They have biased errors due to imbalance between commuting inflows and outflows, and obscure the main variation in unemployment on the urban-rural dimension. Three papers on Incapacity Benefit (IB) analyse the dynamics of change in the stock of claimants, investigating the roles played by health status and labour market conditions. The most recent of these papers examines whether the striking fall in IB claims in Glasgow and other former industrial areas in 2003-08 was the result of official interventions or of improving labour market conditions, concluding that it was mainly the latter. A key ‘supply-side’ assumption was that being unemployed in itself makes people less ‘employable’ – the theory of ‘state-dependence’. The paper on long-term unemployment radically challenges this interpretation. It points out that the literature on the relationship between long-term and short-term unemployment has generally failed to consider the appropriate time-lags or the behaviour of the standard measure of long-term unemployment. It shows that the phenomenon which the theory of state-dependence purports to explain does not occur to any significant extent. Outmigration and housing abandonment are significant effects of local job loss. The paper on housing abandonment demonstrates a statistical relationship across England in 1997 between social housing surplus and ‘real unemployment’, while a further paper challenges the view that there was no longer a deficiency of demand for labour in Glasgow and the Clyde Valley in the 1990s by investigating migration patterns. It demonstrates that net flows between individual Scottish areas and the rest of the UK were to a substantial extent determined by changes in labour demand. A new finding is that little adjustment to employment change occurs through migration within Scotland. The large increase in lone parenthood in Great Britain since the 1960s has been strongly correlated across areas with male worklessness. The US literature suggested that this relationship is causal, and this thesis is investigated in two papers. The earlier of these was the first comprehensive published application of this interpretation to the modern British case. A further paper concludes that falling male employment accounted for around half the rise in lone parenthood in Great Britain in 1971-2001. Two of the papers present a comprehensive picture of the geographical distributions of the different groups of disadvantaged people in the labour market, showing that they all conform to a similar pattern which in turn is related to deficient labour demand.

In this thesis, optimum experimental designs for a statistical model possessing a skewed error distribution are considered, with particular interest in investigating possible parameter dependence of the optimum designs. The skewness in the distribution of the error arises from its assumed structure. The error consists of two components (i) random error, say V, which is symmetrically distributed with zero expectation, and (ii) some type of systematic error, say U, which is asymmetrically distributed with nonzero expectation. Error of this type is sometimes called 'composed' error. A stochastic frontier model is an example of a model that possesses such an error structure. The systematic error, U, in a stochastic frontier model represents the economic efficiency of an organisation. Three methods for approximating information matrices are presented. An approximation is required since the information matrix contains complicated expressions, which are difficult to evaluate. However, only one method, 'Method 1', is recommended because it guarantees nonnegative definiteness of the information matrix. It is suggested that the optimum design is likely to be sensitive to the approximation. For models that are linearly dependent on the model parameters, the information matrix is independent of the model parameters but depends on the variance parameters of the random and systematic error components. Consequently, the optimum design is independent of the model parameters but may depend on the variance parameters. Thus, designs for linear models with skewed error may be parameter dependent. For nonlinear models, the optimum design may be parameter dependent in respect of both the variance and model parameters. The information matrix is rank deficient. As a result, only subsets or linear combinations of the parameters are estimable. The rank of the partitioned information matrix is such that designs are only admissible for optimal estimation of the model parameters, excluding any intercept term, plus one linear combination of the variance parameters and the intercept. The linear model is shown to be equivalent to the usual linear regression model, but with a shifted intercept. This suggests that the admissible designs should be optimal for estimation of the slope parameters plus the shifted intercept. The shifted intercept can be viewed as a transformation of the intercept in the usual linear regression model. Since D_A-optimum designs are invariant to linear transformations of the parameters, the D_A-optimum design for the asymmetrically distributed linear model is just the linear, parameter independent, D_A-optimum design for the usual linear regression model with nonzero intercept. C-optimum designs are not invariant to linear transformations. However, if interest is in optimally estimating the slope parameters, the linear transformation of the intercept to the shifted intercept is no longer a consideration and the C-optimum design is just the linear, parameter independent, C-optimum design for the usual linear regression model with nonzero intercept. If interest is in estimating the slope parameters, and the shifted intercept, the C-optimum design will depend on (i) the design region; (ii) the distributional assumption on U; (iii) the matrix used to define admissible linear combinations of parameters; (iv) the variance parameters of U and V; (v) the method used to approximate the information matrix. Some numerical examples of designs for a cross-sectional log-linear Cobb-Douglas stochastic production frontier model are presented to demonstrate the nonlinearity of designs for models with a skewed error distribution. Torsney's (1977) multiplicative algorithm was implemented in finding the optimum designs.