Cointegration and causal relationships between energy consumption and output: Assessing the evidence from Australia

In this paper, we describe our investigation of the cointegration and causal relationships between energy consumption and economic output in Australia over a period of five decades. The framework used in this paper is the single-sector aggregate production function, which is the first comprehensive approach used in an Australian study of this type to include energy, capital and labour as separate inputs of production. The empirical evidence points to a cointegration relationship between energy and output and implies that energy is an important variable in the cointegration space, as are conventional inputs capital and labour. We also find some evidence of bidirectional causality between GDP and energy use. Although the evidence of causality from energy use to GDP was relatively weak when using the thermal aggregate of energy use, once energy consumption was adjusted for energy quality, we found strong evidence of Granger causality from energy use to GDP in Australia over the investigated period. The results are robust, irrespective of the assumptions of linear trends in the cointegration models, and are applicable for different econometric approaches.

The long-run impact of Information and Communication Technology on economic output: The case of Australia

This paper investigates the cointegration and causal relationships between Information and Communication Technology (ICT) and economic output in Australia using data for about five decades. The framework used in this paper is the single-sector aggregate production function, which is the first comprehensive approach of this kind to include ICT and non-ICT capital and other factors to examine long-run Granger causality. The empirical evidence points to a cointegration relationship between ICT capital and output, and implies that ICT capital Granger causes economic output and multifactor productivity, as does non-ICT capital.

A reassessment of energy and GDP relationship: The case of Australia

This paper investigates the long- and short-run relationships between energy consumption and economic growth in Australia using the bound testing and the ARDL approach. The analytical framework utilized in this paper includes both production and demand side models and a unified model comprising both production and demand side variables. The energy-GDP relationships are investigated at aggregate as well as several disaggregated energy categories, such as coal, oil, gas and electricity. The possibilities of one or more structural break(s) in the data series are examined by applying the recent advances in techniques. We find that the results of the cointegration tests could be affected by the structural break(s) in the data. It is, therefore, crucial to incorporate the information on structural break(s) in the subsequent modelling and inferences. Moreover, neither the production side nor the demand side framework alone can provide sufficient information to draw an ultimate conclusion on the cointegration and causal direction between energy and output. When alternative frameworks and structural break(s) in time series are explored properly, strong evidence of a bidirectional relationship between energy and output can be observed. The finding is true at both the aggregate and the disaggregate levels of energy consumption.

Energy-output linkages in Australia: Implications for emissions reduction policies

The study investigates the long-run and dynamic relationships between energy consumption and output in Australia using a multivariate cointegration and causality framework. Using both Engle-Granger and Johansen cointegration approaches, the study finds that energy consumption and real Gross Domestic Product are cointegrated. The Granger causality tests suggest bidirectional Granger causality between energy consumption and real GDP, and Granger endogeineity in the system. Since the energy sector largely contributes to carbon emissions in Australia, we suggest that direct measures to reduce carbon by putting constraints on the energy consumption would pose significant economic costs for the Australian economy.

The use of metabolomics to monitor simultaneous changes in metabolic variables following supramaximal low volume high intensity exercise

High Intensity Exercise (HIE) stimulates greater physiological remodeling when compared to workload matched low-moderate intensity exercise. This study utilized an untargeted metabolomics approach to examine the metabolic perturbations that occur following two workload matched supramaximal low volume HIE trials. In a randomized order, 7 untrained males completed two exercise protocols separated by one week; 1) HIE150%: 30 x 20s cycling at 150% VO2peak, 40s passive rest; 2) HIE300%: 30 x 10s cycling at 300% VO2peak, 50 s passive rest. Total exercise duration was 30 minutes for both trials. Blood samples were taken at rest, during and immediately following exercise and at 60 minutes post exercise. Gas chromatography-mass spectrometry (GC-MS) analysis of plasma identified 43 known metabolites of which 3 demonstrated significant fold changes (HIE300% compared to the HIE150% value) during exercise, 14 post exercise and 23 at the end of the recovery period. Significant changes in plasma metabolites relating to lipid metabolism [fatty acids: dodecanoate (p=0.042), hexadecanoate (p=0.001), octadecanoate (p=0.001)], total cholesterol (p=0.001), and glycolysis [lactate (p=0.018)] were observed following exercise and during the recovery period. The HIE300% protocol elicited greater metabolic changes relating to lipid metabolism and glycolysis when compared to HIE150% protocol. These changes were more pronounced throughout the recovery period rather than during the exercise bout itself. Data from the current study demonstrate the use of metabolomics to monitor intensity-dependent changes in multiple metabolic pathways following exercise. The small sample size indicates a need for further studies in a larger sample cohort to validate these findings.

Climate change impact assessment: Uncertainty modeling with imprecise probability

Hydrologic impacts of climate change are usually assessed by downscaling the General Circulation Model (GCM) output of large-scale climate variables to local-scale hydrologic variables. Such an assessment is characterized by uncertainty resulting from the ensembles of projections generated with multiple GCMs, which is known as intermodel or GCM uncertainty. Ensemble averaging with the assignment of weights to GCMs based on model evaluation is one of the methods to address such uncertainty and is used in the present study for regional-scale impact assessment. GCM outputs of large-scale climate variables are downscaled to subdivisional-scale monsoon rainfall. Weights are assigned to the GCMs on the basis of model performance and model convergence, which are evaluated with the Cumulative Distribution Functions (CDFs) generated from the downscaled GCM output (for both 20th Century [20C3M] and future scenarios) and observed data. Ensemble averaging approach, with the assignment of weights to GCMs, is characterized by the uncertainty caused by partial ignorance, which stems from nonavailability of the outputs of some of the GCMs for a few scenarios (in Intergovernmental Panel on Climate Change [IPCC] data distribution center for Assessment Report 4 [AR4]). This uncertainty is modeled with imprecise probability, i.e., the probability being represented as an interval gray number. Furthermore, the CDF generated with one GCM is entirely different from that with another and therefore the use of multiple GCMs results in a band of CDFs. Representing this band of CDFs with a single valued weighted mean CDF may be misleading. Such a band of CDFs can only be represented with an envelope that contains all the CDFs generated with a number of GCMs. Imprecise CDF represents such an envelope, which not only contains the CDFs generated with all the available GCMs but also to an extent accounts for the uncertainty resulting from the missing GCM output. This concept of imprecise probability is also validated in the present study. The imprecise CDFs of monsoon rainfall are derived for three 30-year time slices, 2020s, 2050s and 2080s, with A1B, A2 and B1 scenarios. The model is demonstrated with the prediction of monsoon rainfall in Orissa meteorological subdivision, which shows a possible decreasing trend in the future.

Do Measurement Errors in GDP Announcements Cause Output Fluctuations?

This thesis studies empirically whether measurement errors in aggregate production statistics affect sentiment and future output. Initial announcements of aggregate production are subject to measurement error, because many of the data required to compile the statistics are produced with a lag. This measurement error can be gauged as the difference between the latest revised statistic and its initial announcement. Assuming aggregate production statistics help forecast future aggregate production, these measurement errors are expected to affect macroeconomic forecasts. Assuming agents’ macroeconomic forecasts affect their production choices, these measurement errors should affect future output through sentiment. This thesis is primarily empirical, so the theoretical basis, strategic complementarity, is discussed quite briefly. However, it is a model in which higher aggregate production increases each agent’s incentive to produce. In this circumstance a statistical announcement which suggests aggregate production is high would increase each agent’s incentive to produce, thus resulting in higher aggregate production. In this way the existence of strategic complementarity provides the theoretical basis for output fluctuations caused by measurement mistakes in aggregate production statistics. Previous empirical studies suggest that measurement errors in gross national product affect future aggregate production in the United States. Additionally it has been demonstrated that measurement errors in the Index of Leading Indicators affect forecasts by professional economists as well as future industrial production in the United States. This thesis aims to verify the applicability of these findings to other countries, as well as study the link between measurement errors in gross domestic product and sentiment. This thesis explores the relationship between measurement errors in gross domestic production and sentiment and future output. Professional forecasts and consumer sentiment in the United States and Finland, as well as producer sentiment in Finland, are used as the measures of sentiment. Using statistical techniques it is found that measurement errors in gross domestic product affect forecasts and producer sentiment. The effect on consumer sentiment is ambiguous. The relationship between measurement errors and future output is explored using data from Finland, United States, United Kingdom, New Zealand and Sweden. It is found that measurement errors have affected aggregate production or investment in Finland, United States, United Kingdom and Sweden. Specifically, it was found that overly optimistic statistics announcements are associated with higher output and vice versa.

Essays on Labor Market Frictions, Technological Change and Macroeconomic Fluctuations

The dissertation consists of an introductory chapter and three essays that apply search-matching theory to study the interaction of labor market frictions, technological change and macroeconomic fluctuations. The first essay studies the impact of capital-embodied growth on equilibrium unemployment by extending a vintage capital/search model to incorporate vintage human capital. In addition to the capital obsolescence (or creative destruction) effect that tends to raise unemployment, vintage human capital introduces a skill obsolescence effect of faster growth that has the opposite sign. Faster skill obsolescence reduces the value of unemployment, hence wages and leads to more job creation and less job destruction, unambiguously reducing unemployment. The second essay studies the effect of skill biased technological change on skill mismatch and the allocation of workers and firms in the labor market. By allowing workers to invest in education, we extend a matching model with two-sided heterogeneity to incorporate an endogenous distribution of high and low skill workers. We consider various possibilities for the cost of acquiring skills and show that while unemployment increases in most scenarios, the effect on the distribution of vacancy and worker types varies according to the structure of skill costs. When the model is extended to incorporate endogenous labor market participation, we show that the unemployment rate becomes less informative of the state of the labor market as the participation margin absorbs employment effects. The third essay studies the effects of labor taxes on equilibrium labor market outcomes and macroeconomic dynamics in a New Keynesian model with matching frictions. Three policy instruments are considered: a marginal tax and a tax subsidy to produce tax progression schemes, and a replacement ratio to account for variability in outside options. In equilibrium, the marginal tax rate and replacement ratio dampen economic activity whereas tax subsidies boost the economy. The marginal tax rate and replacement ratio amplify shock responses whereas employment subsidies weaken them. The tax instruments affect the degree to which the wage absorbs shocks. We show that increasing tax progression when taxation is initially progressive is harmful for steady state employment and output, and amplifies the sensitivity of macroeconomic variables to shocks. When taxation is initially proportional, increasing progression is beneficial for output and employment and dampens shock responses.

The Structure and Short-Term Development of Finnish Industries in the 1920s and 1930s : An Input-output Approach

Tutkimuksen tavoitteena on tuottaa uutta tietoa Suomen kansantalouden rakenteesta ja lyhyen aikavälin kehityksestä 1920- ja 1930-luvulla. Tutkimus toteutettiin laatimalla kansantaloutta kuvaava panos-tuotostaulu vuodelle 1928 sekä sen laajennus, panos-tuotosmalli. Aineiston avulla kuvataan kansantalouden rakenteellisia riippuvuuksia, tuotannon avaintoimialoja sekä näiden vaikutusta kansantalouteen. Lisäksi tutkimuksessa tarkastellaan kansantalouden tuontiriippuvuutta sekä tuontitullien vaikutusta hintoihin 1930-luvun laman aikana. Tutkimuksen perusteella voitiin identifioida Suomen kansantalouden avaintoimialat vuonna 1928: maatalous, metsätalous, elintarviketeollisuus, puuteollisuus, paperiteollisuus ja rakennustoiminta. Erityisesti elintarviketeollisuuden vahva rooli kansantaloudessa oli kenties yllättävää, erityisesti kun huomioidaan kuinka vähän toimiala on saanut huomiota osakseen taloushistorian tutkimuksessa. Tutkimus osoitti, että Suomen vienti oli pääomavaltaisempaa kuin tuonti. Vaikka tämän tuloksen tulkinta on varauksellinen, tutkimus pystyi osoittamaan ja kvantifioimaan toimialojen työ- ja pääomapanoksen osuuden tuotoksesta yksityiskohtaisesti. Panos-tuotosmallilla arvioitiin puuteollisuuden, paperiteollisuuden ja rakennustoiminnan ajanjaksona 1928-32 tapahtuneen loppukäytön muutoksen vaikutusta kansantalouteen. Merkittävä havainto on, että rakennustoiminnan loppukäytön muutoksella oli erittäin suuri kasvua vähentävä vaikutus koko kansantaloudessa. Talonrakennusinvestointien romahtaminen aiheutti lähes 13 prosentin tuotannon laskun kansantaloudessa. Vaikutus oli jopa suurempi kuin puuteollisuuden viennin romahtamisen. Tulokset osoittavat toisaalta, että yksityisen kulutuksen merkitys kansantaloudelle oli erittäin vahva. Esimerkiksi puuteollisuuden viennin romahtaminen aiheutti yli 4 % tuotannon vähenemisen mutta huomioitaessa mallissa myös yksityisen kulutuksen väheneminen, oli kokonaisvaikutus yli 10 %. Yksityisen kulutuksen huomioiminen mallissa siis yli kaksinkertaisti toimialojen vaikutukset kansantalouteen. Tulokset vahvistivat aiemmissa tutkimuksissa esitettyjä johtopäätöksiä tullipolitiikasta ja osoittivat maatalouteen läheisesti liittyvän elintarviketeollisuuden olleen eniten suojeltu toimiala kansantaloudessa. Muut kotimarkkinoiden toimialat eivät kuitenkaan hyötyneet tullipolitiikasta lamakauden aikana. Panos-tuotoshintamallilla osoitettiin, ettei tullipolitiikka ollut niin onnistunutta kuin aikalaistutkimuksissa väitettiin, vaan tullit korkeintaan pystyivät hidastamaan hintojen alenemista. Tutkimuksen liitteenä esitetään kaikki keskeiset Suomen kansantaloutta vuonna 1928 kuvaavat tilastolliset taulukot, mukaan lukien käyttö- ja tarjontataulukot, panos-tuotostaulukot, panoskertoimet, Leontiefin käänteismatriisi sekä työ- ja pääomapanoskertoimet.

Output feedback control of networked systems with a stochastic communication protocol

This paper addresses an output feedback control problem for a class of networked control systems (NCSs) with a stochastic communication protocol. Under the scenario that only one sensor is allowed to obtain the communication access at each transmission instant, a stochastic communication protocol is first defined, where the communication access is modelled by a discrete-time Markov chain with partly unknown transition probabilities. Secondly, by use of a network-based output feedback control strategy and a time-delay division method, the closed-loop system is modeled as a stochastic system with multi time-varying delays, where the inherent characteristic of the network delay is well considered to improve the control performance. Then, based on the above constructed stochastic model, two sufficient conditions are derived for ensuring the mean-square stability and stabilization of the system under consideration. Finally, two examples are given to show the effectiveness of the proposed method.

Climate forcing on avian life history

In the 21st century, human-induced global climate change has been highlighted as one of the most serious threats to ecosystems worldwide. According to global climate scenarios, the mean temperature in Finland is expected to increase by 1.8 4.0°C by the end of the century. The regional and seasonal change in temperature has predicted to be spatially and temporally asymmetric, where the High-Arctic and Antarctic areas and winter and spring seasons have been projected to face the highest temperature increase. To understand how species respond to the ongoing climate change, we need to study how climate affects species in different phases of their life cycle. The impact of climate on breeding and migration of eight large-sized bird species was studied in this thesis, taking food availability into account. The findings show that climatic variables have considerable impact on the life-history traits of large-sized birds in northern Europe. The magnitude of climatic effects on migration and breeding was comparable with that of food supply, conventionally regarded as the main factor affecting these life-history traits. Based on the results of this thesis and the current climate scenarios, the following not mutually exclusive responses are possible in the near future. Firstly, asymmetric climate change may result in a mistiming of breeding because mild winters and early spring may lead to earlier breeding, whereas offspring are hatching into colder conditions which elevate mortality. Secondly, climate induced responses can differ between species with different breeding tactics (income vs. capital breeding), so that especially capital breeders can gain advantage on global warming as they can sustain higher energy resources. Thirdly, increasing precipitation has the potential to reduce the breeding success of many species by exposing nestlings to more severe post-hatching conditions and hampering the hunting conditions of parents. Fourthly, decreasing ice cover and earlier ice-break in the Baltic Sea will allow earlier spring migration in waterfowl. In eiders, this can potentially lead to more productive breeding. Fifthly, warming temperatures can favour parents preparing for breeding and increase nestling survival. Lastly, the climate-induced phenological changes in life history events will likely continue. Furthermore, interactions between climate and food resources can be complex and interact with each other. Eiders provide an illustrative example of this complexity, being caught in the crossfire between more benign ice conditions and lower salinity negatively affecting their prime food resource. The general conclusion is that climate is controlling not only the phenology of the species but also their reproductive output, thus affecting the entire population dynamics.

Calculating the bound spectrum by path summation in action-angle variables

The density of states n(E) is calculated for a bound system whose classical motion is integrable, starting from an expression in terms of the trace of the time-dependent Green function. The novel feature is the use of action-angle variables. This has the advantages that the trace operation reduces to a trivial multiplication and the dependence of n(E) on all classical closed orbits with different topologies appears naturally. The method is contrasted with another, not applicable to integrable systems except in special cases, in which quantization arises from a single closed orbit which is assumed isolated and the trace taken by the method of stationary phase.

Postoperative Volume Therapy in Cardiac Surgery : Effects on Hemostatic and Circulatory Variables

Background: Patients may need massive volume-replacement therapy after cardiac surgery because of large fluid transfer perioperatively, and the use of cardiopulmonary bypass. Hemodynamic stability is better maintained with colloids than crystalloids but colloids have more adverse effects such as coagulation disturbances and impairment of renal function than do crystalloids. The present study examined the effects of modern hydroxyethyl starch (HES) and gelatin solutions on blood coagulation and hemodynamics. The mechanism by which colloids disturb blood coagulation was investigated by thromboelastometry (TEM) after cardiac surgery and in vitro by use of experimental hemodilution. Materials and methods: Ninety patients scheduled for elective primary cardiac surgery (Studies I, II, IV, V), and twelve healthy volunteers (Study III) were included in this study. After admission to the cardiac surgical intensive care unit (ICU), patients were randomized to receive different doses of HES 130/0.4, HES 200/0.5, or 4% albumin solutions. Ringer’s acetate or albumin solutions served as controls. Coagulation was assessed by TEM, and hemodynamic measurements were based on thermodilutionally measured cardiac index (CI). Results: HES and gelatin solutions impaired whole blood coagulation similarly as measured by TEM even at a small dose of 7 mL/kg. These solutions reduced clot strength and prolonged clot formation time. These effects were more pronounced with increasing doses of colloids. Neither albumin nor Ringer’s acetate solution disturbed blood coagulation significantly. Coagulation disturbances after infusion of HES or gelatin solutions were clinically slight, and postoperative blood loss was comparable with that of Ringer’s acetate or albumin solutions. Both single and multiple doses of all the colloids increased CI postoperatively, and this effect was dose-dependent. Ringer’s acetate had no effect on CI. At a small dose (7 mL/kg), the effect of gelatin on CI was comparable with that of Ringer’s acetate and significantly less than that of HES 130/0.4 (Study V). However, when the dose was increased to 14 and 21 mL/kg, the hemodynamic effect of gelatin rose and became comparable with that of HES 130/0.4. Conclusions: After cardiac surgery, HES and gelatin solutions impaired clot strength in a dose-dependent manner. The potential mechanisms were interaction with fibrinogen and fibrin formation, resulting in decreased clot strength, and hemodilution. Although the use of HES and gelatin inhibited coagulation, postoperative bleeding on the first postoperative morning in all the study groups was similar. A single dose of HES solutions improved CI postoperatively more than did gelatin, albumin, or Ringer’s acetate. However, when administered in a repeated fashion, (cumulative dose of 14 mL/kg or more), no differences were evident between HES 130/0.4 and gelatin.

Early and late electrophysiological effects of distractor frequency in picture naming: Reconciling input and output accounts

The “distractor-frequency effect” refers to the finding that high-frequency (HF) distractor words slow picture naming less than low-frequency distractors in the picture–word interference paradigm. Rival input and output accounts of this effect have been proposed. The former attributes the effect to attentional selection mechanisms operating during distractor recognition, whereas the latter attributes it to monitoring/decision mechanisms operating on distractor and target responses in an articulatory buffer. Using high-density (128-channel) EEG, we tested hypotheses from these rival accounts. In addition to conducting stimulus- and response-locked whole-brain corrected analyses, we investigated the correct-related negativity, an ERP observed on correct trials at fronto-central electrodes proposed to reflect the involvement of domain general monitoring. The wholebrain ERP analysis revealed a significant effect of distractor frequency at inferior right frontal and temporal sites between 100 and 300-msec post-stimulus onset, during which lexical access is thought to occur. Response-locked, region of interest (ROI) analyses of fronto-central electrodes revealed a correct-related negativity starting 121 msec before and peaking 125 msec after vocal onset on the grand averages. Slope analysis of this component revealed a significant difference between HF and lowfrequency distractor words, with the former associated with a steeper slope on the time windowspanning from100 msec before to 100 msec after vocal onset. The finding of ERP effects in time windows and components corresponding to both lexical processing and monitoring suggests the distractor frequency effect is most likely associated with more than one physiological mechanism.

Virus-Specific Cytolytic Antibodies to Nonstructural Protein 1 of Japanese Encephalitis Virus Effect Reduction of Virus Output from Infected Cells

We demonstrate the presence of nonstructural protein 1 (NS1)-specific antibodies in a significant proportion of convalescent-phase human serum samples obtained from a cohort in an area where Japanese encephalitis virus (JEV) is endemic. Sera containing antibodies to NS1 but not those with antibodies to other JEV proteins, such as envelope, brought about complement-mediated lysis of JEV-infected BHK-21 cells. Target cells infected with a recombinant poxvirus expressing JEV NS1 on the cell surface confirmed the NS1 specificity of cytolytic antibodies. Mouse anti-NS1 cytolytic sera caused a complement-dependent reduction in virus output from infected human cells, demonstrating their important role in viral control. Antibodies elicited by JEV NS1 did not cross lyse West Nile virus- or dengue virus-infected cells despite immunoprecipitating the NS1 proteins of these related flaviviruses. Additionally, JEV NS1 failed to bind complement factor H, in contrast to NS1 of West Nile virus, suggesting that the NS1 proteins of different flaviviruses have distinctly different mechanisms for interacting with the host. Our results also point to an important role for JEV NS1-specific human immune responses in protection against JE and provide a strong case for inclusion of the NS1 protein in next generation of JEV vaccines.