The relationship between exchange rate volatility and trade flow has been examined in a number of previous researches. The paper mainly focuses on investigating the impact of exchange rate volatility on export values from Sweden to Germany during 2000:01 and 2011:06. The Auto Regressive Distributed Lag (ARDL) model is employed to obtain the estimates of the long run equilibrium and the short run dynamics, simultaneously. The results indicate that the exchange rate volatility has significant short run effects on export value in majority of estimated industries while its meaningful long run impacts do not appear in any cases. However, applying the “bounds test” approach, the co-integration is also found in more than half cases due to long run impacts of other factors such as foreign income on export earnings.

The rapid growth of gasoline consumption in the USA for the last decades brings much concern to scientists and politicians. Therefore many researchers investigated the influence of the main factors that have an impact on gasoline demand. In our study we tried to estimate gasoline demand in the USA, using national time series data for the period 1984-2010. Gasoline demand function considered in this paper includes price, income, fuel efficiency and gasoline consumption in previous year, as the main explanatory variables. The model is estimated using simultaneous equations and cointegration and error correction model (ECM). The results of both methods show a significant price and income effect on gasoline demand. The price is found inelastic and its impact on gasoline demand is very small, however when we correct for endogeneity of price variable, we obtain higher price elasticity. The results on income elasticities obtained from two methods are dubious, since the two methods gave us the different results. In whole, an income raise will lead to an increase of consumption, gasoline demand is inelastic with respect to income in the short-run, while in the long-run it is found to be elastic according to 2SLS method, while the results of cointegration method indicate that gasoline response to income changes is higher in the short-run than in the long-run. Lag of error term suggests that around 57% of adjustment between short-run and long-run occurs during the first year.

This study estimates an energy sector model consisting of interfuel substitution model and an aggregate energy and non-energy input demand system that incorporates short-run and longrun structural adjustment parameters. The study finds that all fuels in the energy aggregate are Morishima substitutes and that there are significant sectoral variations in magnitude of the elasticities. This indicates that economic instruments should be considered for energy policy but such policies should take into account not only differences in technology used across sectors but also the systematic distribution of costs when the relative prices of fuels change. Estimates of long-run elasticities for aggregate input demands indicate that energy-capital input ratios adjust faster than labour-capital input ratios. This suggests that investment policy should take into consideration tradeoffs between environmental gains and employment implicit in the production structure of the Malawian economy as both capital and labour demands have dynamic interactions with energy in the long-run with potential significant cumulative impacts on the environment. Using results and gaps noted from the partial equilibrium analysis, the study also evaluated general equilibrium impacts of reducing fossil and biomass fuel use by production activities while investing in more hydroelectricity. The results show that carbon emissions and forest resource depletion due to energy use, respectively, can be reduced by imposing environmental taxes aimed at inducing a shift from biomass and fossil fuels to hydroelectricity. More significantly, there are at least three dividends from inducing a shift in the energy mix in that the economy can attain GDP at least equal to the value before imposition of environmental taxes in addition to reducing carbon emissions and deforestation. Further, redistributing the environmental tax revenues to reduce direct taxes on households leads to better income distribution. These findings have direct policy relevance to the contemporary challenges to sustainable development under the added burdens of climate change. Most importantly is what developing countries can do to strategically position themselves in global agreements on financing for climate change adaptation and mitigation. The general equilibrium estimate of direct environmental cost associated with the use of fossil and biomass fuels is close to the moderate estimate of social cost of deforestation in the National Environmental Action Plan (NEAP). This is significant because in the absence of estimates of damages of secondary impacts of both carbon emissions and deforestation, the optimal energy tax as inferred from the general equilibrium model corresponds to the annual growth rate in the economy’s energy intensity. In addition, since short-run to medium term environmental impacts are critical when data on secondary damages are unavailable, it would be prudent to target growth in intensities of use of fuels that contribute to the economy’s footprint on the environment. The study also proposes alternatives to carbon emission taxation that could complement the current legislation on land use by agricultural estates. / Thesis (PhD)--University of Pretoria, 2010. / Agricultural Economics, Extension and Rural Development / unrestricted

<p> This dissertation is concerned with the problems of constructing testable models of the short-run dynamics of urban labour markets, given the currently available data sources. Bimonthly data for manufacturing production workers in U.S. cities were considered the most complete for the purpose. Twenty-nine cities were chosen (Indiana, 1 city; Michigan, 1 city; New York State, 7 cities; Ohio, 8 cities; Pennsylvania, 12 cities). The period of the study, 1964-73, was chosen to avoid changes in data-base definition and to avoid the impact of the oil embargo of late 1973. </p> <p> Two types of model were estimated for each city, with different specifications for each model. The first model consisted of three linear, simultaneous difference equations determining, for each city, the number of hours worked per period (number of employees x number of hours worked per employee), the supply of hours available per period and the average weekly wage rate. When tested empirically this model was successful in explaining all these variables. The second model consisted of five equations, determining the number of people employed per period, the number of hours worked per employee per period, the size of the labour force, the hourly wage rate and the voluntary quit rate from employment. This model was considered the theoretically superior of the two in that it allowed for employers substituting between the number of their employees and the number of hours worked by each employee per period. This model also proved the more empirically successful of the two models. The models were tested using the Two-Stage Least-Squares estimation technique. It is believed that this is the first time that such models have been tested in order to analyse short-run urban labour market behaviour. </p> <p> It was hypothesised that the level of manufacturing production is a major determinant of labour market activity in each city. Unfortunately no short-run urban manufacturing production data are available either for the U.S.A. or elsewhere. This fundamental deficiency in the data base was overcome by the development of a synthetic urban manufacturing production time-series, using national U.S.A. production time-series weighted by the proportions of each of nine manufacturing categories in each city. The technique cannot be validated directly but the results from the models are consistent with the synthetic series being excellent proxies for the true series. </p> <p> The results indicated that the cities all had labour markets that behaved in remarkably similar ways, despite the fact that the labour forces involved ranged in size from 57,000 to 5,558,400 people. In particular the labour markets all exhibited highly stable dynamic behaviour. This result indicated that the labour markets were unlikely to be the generators of boom or slump in their respective cities. When estimated labour market parameters were mapped there appeared to be only weak spatial groupings of the parameter values. Similarly weak groupings appeared when the parameter values were plotted against labour force size. No firm conclusions could be drawn from the groupings. Originally it was intended to model the inter-urban labour market interactions but this proved impossible. All the results are based, therefore, on the assumption that those inter-urban interactions are weak enough to be ignored in the short-run. </p> / Thesis / Doctor of Philosophy (PhD)

As the share of renewable and intermittent energy sources grow and as society becomes more electrified, electricity price volatility becomes one of the most pressing issues. The flexibility of household demand, when faced with price shocks, determines how exposed they will be to price volatility, making the estimation of their short-run price elasticity highly relevant for policymakers. The elasticity was estimated for the hourly demand, the daily demand, and the weekly demand using a difference in difference setup. All estimated elasticities were between -0.10 and -0.19, with the elasticity of hourly demand being the smallest and the elasticity of weekly demand being largest. This implies that household demand is very inelastic but grows in the longer run, even when the longer run is rather short. The elasticity differs between electricity pricing areas. The largest estimated elasticity was in the area which experienced the greatest price shock.

Statistisk processtyrning, SPS, är ett välkänt verktyg som används för kvalitetsförbättringar inom organisationer världen över. De senaste åren har tillverkande organisationer tenderat att gå mot kortare serier, vilket medför en problematik när de vill tillämpa statistiska metoder som är utvecklade för traditionell masstillverkning. Framgångsfaktorer för implementering av SPS vid små serier är ett relativt outforskat område och kräver därför ytterligare forskning. Syftet med denna studie var att ta fram en modell över hur SPS framgångsrikt kan implementeras av organisationer med små serier och en stor detaljflora. För att besvara syftet genomfördes en fallstudie med både kvantitativ och kvalitativ metod. Deltagande observationer och en workshop med 15 deltagare utfördes för att identifiera existerande variationer samt definiera nuläget i det avgränsade produktionsflödet, vars processer studerades i studien. Tre produktfamiljer och kritiska parametrar som representerade produktkvalitén valdes ut för att följas upp i styrdiagram. En mätsystemanalys utfördes för att undersöka om de mätdon som i stor utsträckning användes för kvalitetskontroll i processen var tillförlitliga. Styrdiagram upprättades anpassade för små serier och statistiska analyser utfördes för att undersöka om SPS var en användbar metod för kvalitetsförbättringar i processer med små serier. En kvalitativ benchmark med fyra deltagande organisationer utfördes även för att ta del av deras erfarenheter relaterat till implementering och arbete med SPS.  Resultatet visade att den studerade organisationen behöver utföra förändringar gällande arbetsmetoder för kvalitetskontroll samt hantering av processer och mätsystem. Det finns även behov av ett omfattande förbättringsarbete, för att eliminera det flertalet orsaker till systematiska variationer som identifierades påverka processerna och produktkvalitén. Dessa förändringar krävs innan en implementering av SPS kan genomföras. Verktyg inom SPS visade sig med framgång kunna användas för att förbättra processer med små serier, vid användning av standardiserade styrdiagram som möjliggör analys av flera produkter i samma diagram. Processer med små serier och en stor detaljflora medför en utökad komplexitet vid statistiska analyser och visar tecken på ett flertal svårigheter som ökar risken för en fallerad implementering.  Utifrån analyser av det kvalitativa och kvantitativa resultatet skapades en modell med 15 framgångsfaktorer för implementering av SPS vid små serier. Faktorerna bör följas av organisationer med små serier som vill lyckas med att implementera SPS. Framgångsfaktorerna är följande: (1) Var beredd på en kulturförändring som kräver att SPS vävs in i hela organisationen, (2) Förmedla ett tydligt mål och hållbar strategi för arbetet med SPS, (3) Skapa ett utbrett engagemang i hela organisationen, (4) Utse en SPS-koordinator, (5) Inför utbildning och uppföljning från start, (6) Skapa tvärfunktionella team, (7) Främja samarbete och delaktighet under förbättringsarbetet, (8) Ställ krav på ett dugligt mätsystem, (9) Utför en pilotstudie där det finns intresse, (10) Identifiera kritiska processer, produktfamiljer och parametrar, (11) Börja med att lära känna processerna, (12) Upprätta standardiserade styrdiagram, (13) Tolkning och analys av styrdiagram utförs enligt Montgomerys metod för statistiska analyser, (14) Sträva efter stabila processer, (15) Utför kontinuerlig uppföljning. / Statistical process control, SPC, is a widely used technique for quality improvements by companies all over the world. The current trend in manufacturing organizations is directed towards shorter productions runs, which cause problems when applying traditional statistical methods developed for SPC on mass production runs. The critical factors for a successful implementation of SPC on short runs are still not fully explored and require further research. The main purpose of this study was to present a conceptual framework that illustrates the successful implementation of SPC in organizations with short runs and extensive product portfolio. In order to answer the research questions, a case study research methodology with both quantitative and qualitative methods was used. Participant observations and a workshop including 15 participators were performed in order to identify existing process variability’s and current state of the studied production processes.  Three product families and key quality characteristics of each product were chosen to be monitored in control charts, based on scrap costs and staff experiences of the production process.  A measurement system analysis was used to determine if the gauges, used to make measurement quality controls, were capable. Control charts were constructed and adjusted to short production runs. Statistical analysis was then made on the information gathered through the control charts to determine if statistical tools within SPC was useful for quality improvements on short production runs.  Also a qualitative benchmark was performed with four manufacturing companies to take part of their experiences and knowledge related to the implementation and application of SPC.  The findings indicate that the studied organization needs to improve working methods related to quality inspections and monitoring of the production processes. The organization also needs to improve the measurement system and make an extensive work of improvement to reduce the many identified special causes of variation that affects the processes and product quality, before implementing SPC in the organization. Findings showed that SPC tools and techniques successfully can be adopted to improve short run production processes when using standardized control charts for different product types. Short run production processes involve more complex statistical analysis which could inhibit the success of an implementation of SPC.   The analysis of the qualitative and quantitative findings resulted in a framework including 15 critical success factors for the implementation of SPC in short production runs. All the following critical success factors should be taken into account by organizations with short runs that aspire a successful implementation of SPC: (1) Be ready to make a cultural change including the recognition of the importance of SPC within the whole organization, (2) Communicate a clear goal and long-term strategy, (3) Create motivation and commitment from top management to operators on the shop floor, (4) Select a SPC coordinator, (5) Introduce a training programme with feedback from start, (6) Create cross-functional teams, (7) Stimulate cooperation and participation within the work of improvements, (8) Ensure a capable measurement system, (9) Perform a pilot project with enthusiastic employees, (10) Identify critical processes, product families and key quality characteristics, (11) Focus on exploring process behaviors, (12) Construct standardized control charts, (13) Interpret and analyze control charts according to Montgomery’s method for statistical analysis, (14) Attempt to obtain processes in control, (15) Perform continuous follow ups.

The study examines the price elasticity of demand for cigarettes in the short- and long run in Sweden. The time period for the study is 17 years and covers the years 1996-2012. The results of the study shows that the price elasticity of demand for cigarettes in the long run is higher than in the short run for the Swedish consumers, which is in line with previous studies in the area. The fact that the price elasticity of demand for cigarettes is higher in the long run, indicates that the substitution effect has a significant impact on the price elasticity of demand for cigarettes in the long run. The study was conducted in two parts where the authors investigated the effect of cigarette tax on cigarette prices and in addition the cigarette prices impact on the demand for cigarettes in Sweden. The combined result of the study demonstrates that increasing the cigarette tax by 10 per cent means that the demand for cigarettes is reduced by 5 per cent, while government revenues from the cigarette tax will increase by 4.5 per cent. The result in this paper shows why the state's incentive to raise the cigarette tax is twofold, since a tax increase will generate health benefits through reduced consumption and generate increased revenues to the state. These incentives are also shown to have a greater impact in the long term. / Studien undersöker efterfrågans priselasticitet på cigaretter på kort- och lång sikt i Sverige. Tidsperioden för undersökningen är 17 år och omfattar åren 1996-2012. Studiens resultat visar att efterfrågans priselasticitet på lång sikt är högre än på kort sikt för de Svenska konsumenterna, vilket ligger i linje med tidigare studier inom ämnet. Det faktum att priselasticiteten för cigaretter är högre på lång sikt indikerar på att substitutionseffekten har betydande effekt för efterfrågans priselasticitet på cigaretter på lång sikt. Studien har genomförts i två delar där författarna undersökt cigarettskattens effekt på cigarettpriset och i sin tur cigarettprisets effekt på efterfrågan på cigaretter i Sverige. Det kombinerade resultatet i studien påvisar att en ökning av cigarettskatten med 10 procent medför att efterfrågan på cigaretter minskar med 5 procent, samtidigt som statens intäkter från cigarettskatten ökar med 4,5 procent. Resultatet i denna uppsats visar därför att statens incitament till att höja cigarettskatten är tvådelad, då en skatteökning genererar hälsovinster genom minskad konsumtion samt genererar ökade intäkter till staten och att dessa incitament har en större påverkan på lång sikt.

This thesis presents three essays, each seeking to deepen our understanding of labour markets. The first essay studies the response of real wages and hours of new hires to the business cycle during the UK’s Great Recession. The second essay analysis in how far the assumption of rational expectations in the Mortensen-Pissarides model is required for the economy to converge to an equilibrium. In particular, it asks if it is possible for economic agents to use simple linear forecast rules and still ensure convergence to the rational expectations equilibrium. The final essay seeks to determine whether labour income shares at the sectoral level are constant across countries, as is usually assumed in the literature, and whether this assumption quantitatively matters. Therefore, it takes the input-output structures across countries into account, and conducts a development accounting exercise. Real wages and hours in the Great Recession: Evidence from firms and their entry-level jobs Using employer-employee panel data, I provide novel facts on how real wages and working hours within jobs responded to the UK’s Great Recession. In contrast to previous studies, my data enables me to address the cyclical composition of jobs. I show that firms were able to respond to the Great Recession with substantial real wage cuts and by recruiting more part-time workers. A one percentage point increase in the unemployment rate led to an average decline in real hourly wages of 2.8 per cent for new hires and 2.6 per cent for job stayers. Hours of new hires in entry-level jobs were also substantially procyclical, while job-stayer hours were nearly constant. My findings suggest that models assuming rigid labour costs of new hires are not helpful for understanding the behaviour of unemployment over the business cycle. Unemployment and econometric learning I apply well-known results of the econometric learning literature to the Mortensen-Pissarides real business cycle model. Agents can always learn the unique rational expectations equilibrium (REE), for all possible well-defined sets of parameter values, by using the minimum-state-variable solution to the model and decreasing gain learning. From this perspective, the assumption of rational expectations in the model could be seen as reasonable. But using a parametrisation with UK data, simulations show that the speed of convergence to the REE is slow. This type of learning dampens the cyclical response of unemployment to small structural shocks. Measuring sectoral income shares: Accounting for input-output structures across countries I use input-output tables to measure the labour income shares of the goods and the services sector for a large cross-section of mostly developed countries. I present two novel findings: sectoral labour income shares significantly increase with the level of development, and within-country differences between these income shares are uncorrelated with the level of development. These cross-country differences are not caused by variation in the input-output structure or final demand, but originate at the production-side of the economy. I measure sectoral total factor productivity using a development accounting framework to assess the quantitative importance of my findings. The goods sector of less developed countries is relatively less productive than the services sector; assuming that the values of the sectoral labour income shares across countries are identical to their corresponding U.S. values leads to an underestimation of productivity differences across countries. All findings are robust to different adjustments for the labour income of the self-employed.

Exchange rate economics has achieved substantial development in the past few decades. Despite extensive research, a large number of unresolved problems remain in the exchange rate debate. This dissertation studied three puzzling issues aiming to improve our understanding of exchange rate behavior. Chapter Two used advanced econometric techniques to model and forecast exchange rate dynamics. Chapter Three and Chapter Four studied issues related to exchange rates using the theory of New Open Economy Macroeconomics. Chapter Two empirically examined the short-run forecastability of nominal exchange rates. It analyzed important empirical regularities in daily exchange rates. Through a series of hypothesis tests, a best-fitting fractionally integrated GARCH model with skewed student-t error distribution was identified. The forecasting performance of the model was compared with that of a random walk model. Results supported the contention that nominal exchange rates seem to be unpredictable over the short run in the sense that the best-fitting model cannot beat the random walk model in forecasting exchange rate movements. Chapter Three assessed the ability of dynamic general-equilibrium sticky-price monetary models to generate volatile foreign exchange risk premia. It developed a tractable two-country model where agents face a cash-in-advance constraint and set prices to the local market; the exogenous money supply process exhibits time-varying volatility. The model yielded approximate closed form solutions for risk premia and real exchange rates. Numerical results provided quantitative evidence that volatile risk premia can endogenously arise in a new open economy macroeconomic model. Thus, the model had potential to rationalize the Uncovered Interest Parity Puzzle. Chapter Four sought to resolve the consumption-real exchange rate anomaly, which refers to the inability of most international macro models to generate negative cross-correlations between real exchange rates and relative consumption across two countries as observed in the data. While maintaining the assumption of complete asset markets, this chapter introduced endogenously segmented asset markets into a dynamic sticky-price monetary model. Simulation results showed that such a model could replicate the stylized fact that real exchange rates tend to move in an opposite direction with respect to relative consumption.

This study empirically examines the impact of monetary policy on economic growth in three East African countries (Uganda, Kenya and Tanzania). The role of monetary policy in promoting economic growth remains empirically an open research question, as both the empirical and theoretical underpinnings are not universal, and the results remain varying, inconsistent, and inconclusive. This study may be the first of its kind to examine in detail the impact of monetary policy on economic growth in Uganda, Kenya and Tanzania – using the autoregressive distributed lag (ARDL) bounds-testing approach. This study used two proxies of monetary policy, namely, money supply and interest rate, to examine this linkage. The results were found to differ from country to country and over time. The Uganda empirical results reveal that money supply has a positive impact on economic growth, both in the short run and in the long run. However, interest rate was found to have a positive impact on economic growth only in the short run. In the long run, interest rate has no significant impact on economic growth. In Kenya, both short-run and long-run empirical results support monetary policy neutrality, implying that monetary policy has no effect on economic growth – both in the short run and in the long run. The results from Tanzania also reveal no impact of monetary policy on economic growth in the long run – irrespective of the proxy used to measure monetary policy. However, the short-run results only reveal no impact of monetary policy on economic growth only when the interest rate is used as a proxy for monetary policy. When money supply is used to measure monetary policy, a negative relationship between monetary policy and economic growth is found to dominate. Overall, the study finds that monetary policy is only relevant for economic growth in Uganda and only when money supply is used as monetary policy variable. Therefore this study recommends a money supply based monetary policy framework for Uganda. The study findings also suggest that monetary policy may not be a panacea for economic growth in Kenya and Tanzania. / Economics / M. Com. (Economics)