By combining two of the central paradigms of causality, namely counterfactual reasoning and probability-raising,we introduce a probabilistic notion of cause in Markov chains. Such a cause consists of finite executions of the probabilistic system after which the probability of an ω-regular effect exceeds a given threshold. The cause, as a set of executions, then has to cover all behaviors exhibiting the effect. With these properties, such causes can be used for monitoring purposes where the aim is to detect faulty behavior before it actually occurs. In order to choose which cause should be computed, we introduce multiple types of costs to capture the consumption of resources by the system or monitor from different perspectives, and study the complexity of computing cost-minimal causes.

This thesis aims to explore the time variation of liquidity and transaction prices in the Swedishcommercial real estate market. The purpose is to contribute with insights about price dynamics and liquidity on the Swedish commercial real estate transaction market. A price index was therefore estimated based on the output of a hedonic regression model. The model controls for different locations, segments and years and further includes variables controlling for size, portfolio transactions and investor nationality. The regression model is based on transaction data provided by Cushman & Wakefield which consists of 10 194 observations over a 20-year period between the years 2003-2023. Further the relationship between transaction prices and liquidity was investigated. The liquidity measure used is turnover rate which was calculated for each year based on data from Statistics Sweden (SCB). Granger causality tests were conducted for different geographic aggregation levels to explore if liquidity can predict transaction prices and vice versa. The results show that market liquidity in terms of turnover rate in city and regional locations can be used to forecast the development of transaction prices and therefore“leads” the price development. The test results, in combination with a correlation analysis that showed strong correlation between prices and previous year’s turnover rates, suggests evidence of a sequential relationship between the variables. For the nation as a whole and for the rural location, the results of the causality tests were insignificant and the hypothesis that there does not exist a Granger causality between price and turnover could not be rejected. It was also concluded that since liquidity leads prices, information about turnover rates can be used to help forecast property cycles in the short term. / Detta examensarbete syftar till att undersöka sambandet mellan likviditet och transaktionspriser på den svenska kommersiella fastighetsmarknaden. Syftet är att bidra med insikter om prisdynamik och likviditet på den svenska kommersiella fastighetstransaktionsmarknaden. Ett prisindex estimerades baserat på en hedonisk regressionsmodell. Modellen estimerar transaktionspriser för olika geografiska delmarknader, segment och år och inkluderar vidare variabler som kontrollerar för storlek, portföljtransaktioner och investerarnationalitet. Regressionsmodellen är baserad på transaktionsdata från Cushman & Wakefield som består av 10 194 observationer under en 20-årsperiod mellan åren 2003 och 2023. Vidare undersöktes sambandet mellan transaktionspriser och likviditet. Likviditetsmåttet som används är omsättningsandel som beräknats för respektive år baserat på data från SCB. Test av Grangerkausalitet genomfördes för olika geografiska delmarknader för att undersöka om likviditet kanprediktera transaktionspriser och vice versa. Resultaten visar att marknadslikviditet i form avomsättningsandel i storstäder och regioner kan användas för att prognostisera utvecklingen avtransaktionspriser och därmed "leder" prisutvecklingen. Testresultaten, i kombination med enkorrelationsanalys som visade på en stark korrelation mellan priser och föregående årsomsättningsandelar, tyder på att det finns ett sekventiellt samband mellan variablerna. För landet som helhet och för landsbygden gav kausalitetstesterna inget signifikant resultat och hypotesen att inget kausalitetssamband existerar mellan likviditet och priser kunde därmed inte förkastas. En annan slutsats som drogs var att eftersom likviditet leder priserna kan information om omsättningsförändring användas för att prognostisera fastighetscykler på kort sikt.

Keyword analysis in scientific articles is a method used to identify and evaluate the importance and relevance of specific words or phrases (keywords) within scientific literature. The primary goal of keyword analysis is to uncover the core themes, research trends, and conceptual frameworks within a given field or across multiple disciplines. It helps researchers understand scientific discourse's focus and ideas' evolution over time. This thesis performs keyword analysis on a repository of scientific publications through a combination of methods. It starts with extracting the available keywords, and it deals with the missing keywords data through data augmentation. Then, it utilizes a variety of statistical methods to gain insight into the publications. The study employs an implementation of LDA topic modeling to accurately categorize keywords into thematic groups, a Vector autoregression to explore keyword relationships, and temporal dynamics of keywords. Next, the research further examines the interdisciplinary connectivity of keywords, clarifying the collective nature of modern science. In conclusion, the thesis presents a comprehensive framework for keyword analysis in scientific literature, through a blend of data augmentation, natural language processing, temporal dynamics, and interdisciplinary examination, the study provides a robust tool for understanding the development and structure of scientific literature. The findings of this research have important implications for scholars, it allows navigating the vast amount of scientific literature more effectively and to discern the most influential ideas and trends shaping target fields. The methodologies implemented here offer an opportunity for any studies to methodologically search, extract, and identify keywords to find relevant papers and interpret the complex landscape of scientific communication. / Nyckelordsanalys i vetenskapliga artiklar är en metod som används för att identifiera och utvärdera vikten och relevansen av specifika ord eller fraser (nyckelord) inom vetenskaplig litteratur. Det primära målet med nyckelordsanalys är att avslöja kärnteman, forskningstrender och konceptuella ramverk inom ett givet fält eller över flera lämnar. Det hjälper forskare att förstå den vetenskapliga diskursens fokus och idéernas utveckling över tid. Denna avhandling utför nyckelordsanalys på ett arkiv av vetenskapliga publikationer genom en kombination av metoder. Den börjar med att extrahera de tillgängliga nyckelorden och hanterar de saknade nyckelordsdata genom dataaugtation. Därefter använder den en mängd statistiska metoder för att få insikt i publikationerna. Studien använder en implementering av LDA-ämnesmodellering för att noggrant kategorisera nyckelord i tematiska grupper, en vektorautoregression för att utforska nyckelordsrelationer och tidsmässig dynamik av nyckelord. Nästa steg i forskningen är att ytterligare undersöka den tvärvetenskapliga kopplingen mellan nyckelord, vilket klargör den kollektiva naturen av modern vetenskap. Sammanfattningsvis presenterar avhandlingen ett omfattande ramverk för nyckelordsanalys i vetenskaplig litteratur. Genom en blandning av dataaugmentation, naturlig språkbehandling, tidsmässig dynamik och tvärvetenskaplig undersökning, erbjuder studien ett robust verktyg för att förstå utvecklingen och strukturen av vetenskaplig litteratur. Forskningens resultat har viktiga implikationer för forskare; det möjliggör effektivare navigering i den omfattande mängden vetenskaplig litteratur och att urskilja de mest inflytdrikelserika idéerna och trenderna som formar målfälten. De metoder som införas här erbjuder en möjlighet för vilken studie som helst att metodiskt söka, extrahera och identifiera nyckelord för att hitta relevanta artiklar och tolka det komplexa landskapet av vetenskaplig kommunikation.

Visual attention improves sensory processing, as well as perceptual readout and behavior. Over the last decades, many proposals have been put forth to explain how attention affects visual neural processing. These include the modulation of neural firing rates and synchrony, neural tuning properties, and rhythmic, subthreshold activity. Despite the wealth of knowledge provided by previous studies, the way attention shapes interactions between cortical layers within and between visual sensory areas is only just emerging. To investigate this, we studied neural signals from macaque V1 and V4 visual areas, while monkeys performed a covert, feature-based spatial attention task. The data were simultaneously recorded from laminar electrodes disposed normal to cortical surface in both areas (16 contacts, 150 μm inter-contact spacing). Stimuli presentation was based on the overlap of the receptive fields (RFs) of V1 and V4. Channel depths alignment was referenced to laminar layer IV, based on spatial current source density and temporal latency analyses. Our analyses mainly focused on the study of Local Field Potential (LFP) signals, for which we applied local (bipolar) re-referencing offline. We investigated the effects of attention on LFP spectral power and laminar interactions between LFP signals at different depths, both at the local level within V1 and V4, and at the inter-areal level across V1 and V4. Inspired by current progress from literature, we were interested in the characterization of frequency-specific laminar interactions, which we investigated both in terms of rhythmic synchronization by computing spectral coherence, and in terms of directed causal influence, by computing Granger causalities (GCs). The spectral power of LFPs in different frequency bands showed relatively small differences along cortical depths both in V1 and in V4. However, we found attentional effects on LFP spectral power consistent with previous literature. For V1 LFPs, attention to stimuli in RF location mainly resulted in a shift of the low-gamma (∼30-50 Hz) spectral power peak towards (∼3-4 Hz) higher frequencies and increases in power for frequency bands above low-gamma peak frequencies, as well as decreases in power below these frequencies. For V4 LFPs, attention towards stimuli in RF locations caused a decrease in power for frequencies < 20 Hz and a broad band increase for frequencies > 20 Hz. Attention affected spectral coherence within V1 and within V4 layers in similar way as the spectral power modulation described above. Spectral coherence between V1 and V4 channel pairs was increased by attention mainly in the beta band (∼ 15-30 Hz) and the low-gamma range (∼ 30-50 Hz). Attention affected GC interactions in a layer and frequency dependent manner in complex ways, not always compliant with predictions made by the canonical models of laminar feed-forward and feed-back interactions. Within V1, attention increased feed-forward efficacy across almost all low-frequency bands (∼ 2-50 Hz). Within V4, attention mostly increased GCs in the low and high gamma frequency in a 'downwards' direction within the column, i.e. from supragranular to granular and to infragranular layers. Increases were also evident in an ‘upwards’ direction from granular to supragranular layers. For inter-areal GCs, the dominant changes were an increase in the gamma frequency range from V1 granular and infragranular layers to V4 supragranular and granular layers, as well as an increase from V4 supragranular layers to all V1 layers.

Η παρούσα διατριβή ασχολείται με δύο ιδιαιτέρως σημαντικά και διαχρονικά επίκαιρα ζητήματα στην ανάλυση χρονολογικών σειρών, τα οποία εντάσσονται, υπό ευρεία έννοια, στο πεδίο της Μακροοικονομετρίας. Ειδικότερα, μελετώνται θέματα και μεθοδολογίες ή τεχνικές ιδιαίτερα χρήσιμες για εκείνους τους ερευνητές, οι οποίοι επικεντρώνονται στην ανάλυση της συμπεριφοράς των συναθροιστικών (aggregate) μεγεθών της οικονομίας, βασιζόμενοι στη χρήση δεδομένων χρονοσειρών ή πιο απλά χρονοσειρές (time series). Το πρώτο ζήτημα αφορά στη μελέτη της δυναμικής αλληλεξάρτησης ανάμεσα σε μακροοικονομικές μεταβλητές κάτω από την υιοθέτηση ενός πολλαπλού πλαισίου ανάλυσης χρονοσειρών. Το ενδιαφέρον εστιάζεται κυρίως στην γενικευμένη ή εκτεταμένη έννοια της αιτιότητας κατά Granger, δηλαδή στην επέκταση της τυπικής έννοιας της αιτιότητας κατά Granger σε μεγαλύτερους του ενός ή σε πολλαπλούς ορίζοντες πρόβλεψης. Το δεύτερο ζήτημα αφορά στην παρουσία μη-γραμμικών χαρακτηριστικών σε μακροοικονομικές χρονοσειρές, καθώς και την υποδειγματοποίηση της μη-γραμμικότητας με τη χρήση μη-γραμμικών οικονομετρικών μοντέλων. Επικεντρώνεται δε ιδιαίτερα στον έλεγχο μοναδιαίας ρίζας κάτω από την εναλλακτική υπόθεση της στασιμότητας γύρω από μη-γραμμικές τάσεις της μορφής τάσεων ομαλής μετάβασης (smooth transition trends) στις μακροοικονομικές χρονοσειρές. Ουσιαστικά, η διατριβή διακρίνεται σε δύο κεφάλαια. Στο Κεφάλαιο 1 παρουσιάζεται η τυπική έννοια της αιτιότητας κατά Granger, καθώς και η γενικευμένη ή εκτεταμένη έννοια της αιτιότητας ή η αιτιότητα σε πολλαπλούς ορίζοντες (multi-horizon causality), στο πλαίσιο των διανυσματικών αυτοπαλίνδρομων υποδειγμάτων (VAR). Η τυπική έννοια της αιτιότητας κατά Granger περιορίζεται στη βελτίωση της προβλεψιμότητας σε ορίζοντα πρόβλεψης μίας περιόδου (one-step ahead), ενώ λαμβάνει υπ'όψιν μόνο τις άμεσες ροές πληροφόρησης μεταξύ των μεταβλητών ενδιαφέροντος (direct causality). Ωστόσο, σε υποδείγματα VAR με περισσότερες από δύο μεταβλητές η τυπική έννοια της αιτιότητας μπορεί να επεκταθεί με την μελέτη της βελτίωσης της προβλεψιμότητας σε μεγαλύτερους του ενός ορίζοντες πρόβλεψης. Σε μία περίπτωση όπως η τελευταία, πλην της άμεσης αιτιότητας, δύνανται να μελετηθούν και οι έμμεσες σχέσεις αιτιότητας (indirect causality) που ενδέχεται να προκύψουν μέσω των πρόσθετων μεταβλητών του συστήματος. Το θεωρητικό πλαίσιο της γενικευμένης έννοιας της αιτιότητας που παρουσιάζει η παρούσα διατριβή έχει αναπτυχθεί από τους Dufour and Renault (1998). Παράλληλα, δίνεται ιδιαίτερη βαρύτητα σε δύο πρόσφατες μεθόδους στατιστικής επαγωγής αιτιωδών σχέσεων κατά Granger σε πολλαπλούς ορίζοντες, οι οποίες παρέχουν πρόσθετη πληροφόρηση σχετικά με τη δυναμική αλληλεξάρτηση οικονομικών χρονοσειρών, και πιο συγκεκριμένα σχετικά με τον άμεσο ή έμμεσο χαρακτήρα των αιτιωδών σχέσεων, το διαχωρισμό μεταξύ βραχυχρόνιας και μακροχρόνιας (μη)-αιτιότητας, καθώς και τις πιθανές χρονικές υστερήσεις της αιτιότητας. Τέλος, στα πλαίσια του Κεφαλαίου 1, ερευνάται η δυνατότητα εφαρμογής των μεθόδων αυτών μέσω εμπειρικών εφαρμογών πάνω σε δύο διαχρονικά ζητήματα αιτιωδών σχέσεων ανάμεσα σε οικονομικές μεταβλητές. Στο Κεφάλαιο 2 παρουσιάζονται υποδείγματα ομαλής μετάβασης, καθώς και έλεγχοι μοναδιαίας ρίζας οι οποίοι επιτρέπουν την στασιμότητα γύρω από ομαλές ή βαθμιαίες μεταβάσεις κάτω από την εναλλακτική υπόθεση. Κύριο χαρακτηριστικό των υποδειγμάτων ομαλής μετάβασης είναι η παρουσία μη-γραμμικών τάσεων στη διαχρονική εξέλιξη των χρονοσειρών. Κεντρικό ρόλο στα υποδείγματα αυτά κατέχουν οι διαρθρωτικές μεταβολές (structural changes) στην προσδιοριστική τάση, οι οποίες, δεδομένου ότι αντιπροσωπεύουν μεταβολές της συναθροιστικής συμπεριφοράς, υποδειγματοποιούνται με τη χρήση ενός προσδιοριστικού στοιχείου το οποίο επιτρέπει την βαθμιαία αντί της στιγμιαίας προσαρμογής. Οι έλεγχοι μοναδιαίας ρίζας, οι οποίοι επιτρέπουν περισσότερη ευελιξία στην συνάρτηση της τάσης σε σχέση με την γραμμική εξειδίκευση της προσδιοριστικής τάσης που χρησιμοποιούν οι τυπικοί έλεγχοι μοναδιαίας ρίζας, αποτελούν το επίκεντρο μελέτης του Κεφαλαίου 2 της διατριβής. Η αναγκαιότητα υιοθέτησης πρόσθετων ελέγχων μοναδιαίας ρίζας, όπως οι έλεγχοι μοναδιαίας ρίζας οι οποίοι επιτρέπουν στασιμότητα γύρω από ομαλές μεταβάσεις κάτω από την εναλλακτική υπόθεση, ισχυροποιείται από τα αποτελέσματα της εφαρμογής των ελέγχων αυτών σε ένα σύνολο οικονομικών χρονοσειρών. / This thesis discusses two central research topics in applied time series econometrics that generally belong in the field of Macroeconometrics. In particular, we investigate issues and methods which are of interest to those researchers who want to analyze economic problems or economic aggregates by means of time series data. The first topic deals with the dynamic interrelationships between sets of theory related variables in a multiple time series context. Research interest is primarily focused on the generalized or extended notion of Granger causality, that is the extension of the standard Granger causality concept to higher forecast horizons. The second topic deals with nonlinear behavior of macroeconomic time series, as well as the modelling of nonlinearities in economic time series using nonlinear econometric models. Specific attention is paid to unit root tests that allow stationarity around nonlinear trends in the form of smooth transitions under the alternative. The dissertation consists of two chapters. The first chapter presents the standard concept of Granger causality, along with the generalized or extended notion of causality, also known as multiple-horizon causality, in the vector autoregressive (VAR) framework. The standard notion of Granger causality restricts prediction improvement to a forecast horizon of one period, while it considers only direct flows of information between the variables of interest. However, in VAR models with more than two variables, the concept of standard Granger causality can be extended by studying prediction improvement at forecast horizons greater than one. If this is the case, then, except for direct causality, indirect flows of information might be revealed through the additional variables of the system. The theoretical framework of the extended concept of causality which is presented in the present dissertation has been developed by Dufour and Renault (1998). In addition, special attention is paid to two recent methods for testing hypothesis of non-causality at various horizons which can provide further information on the dynamic interaction of time series, and more specifically on the direct or indirect nature of causal effects, the distinction between short-run and long-run (non)-causality, as wells as the possibility of causal delays. Finally, the potential implementation of these methods is examined through empirical applications on causality relations among different sets of economic variables. Chapter 2 presents smooth transition (STR) trend models, as well as unit root tests that allow stationarity around smooth transitions under the alternative. Smooth transition regression models presume the presence of nonlinear trends in the long-run evolution of time series. A key feature of these models is the presence of structural changes in the deterministic trend which, given that they represent changes in aggregate behavior (economic aggregates), are modelled through a deterministic component that permits gradual rather than instantaneous adjustment between regimes. Unit root tests that permit a more versatile trend function in the unit root procedure, rather than the standard linear trends, are the main concern of Chapter 2. The necessity of employing additional unit root tests, such as unit root tests that allow stationarity around smooth transitions under the alternative, becomes evident through the unit root test results that are observed in an application in a set of economic time series.

In this study, linear and nonlinear Granger causality tests are used to examine the dynamics, including return to return and volume to volume relationships, between warrants and their underlying stocks in Taiwan Stock Exchange (TSEC). Results of previous studies are mixed and they only focus on linear relationship between the two markets. Here we take nonlinear relationship into consideration to assist in investigating what the direction of information flow is. We use intraday five-minute high frequency data and the result tells that, overall, for both return to return and volume to volume relations, there is bidirectional but asymmetry linear causality and weak unidirectional nonlinear causality from stock to warrant market between these two markets. Combining the linear and nonlinear results we conclude that the direction of information flow is mainly from stock market to warrant market.

Although it has been well established that abnormal group delay is a real physical phenomenon and is not in violation of Einstein causality, there has been little investigation into whether or not such abnormal behaviour can be used to reduce signal latency in practical communication systems in the presence of noise. In this thesis, we use time-varying probability of error to determine if abnormal group delay “channels” can offer reduced signal latency. Since the detection system plays a critical role in the analysis, three important detection systems are considered: the correlation, matched filter and envelope detection systems. Our analysis shows that for both spatially negligible microelectronic systems and spatially extended microwave systems, negative group delay “channels” offer reduced signal latency as compared to conventional “channels”. The results presented in the thesis can be used to design a new generation of electronic and microwave interconnects with reduced or eliminated signal latency.

Although it has been well established that abnormal group delay is a real physical phenomenon and is not in violation of Einstein causality, there has been little investigation into whether or not such abnormal behaviour can be used to reduce signal latency in practical communication systems in the presence of noise. In this thesis, we use time-varying probability of error to determine if abnormal group delay “channels” can offer reduced signal latency. Since the detection system plays a critical role in the analysis, three important detection systems are considered: the correlation, matched filter and envelope detection systems. Our analysis shows that for both spatially negligible microelectronic systems and spatially extended microwave systems, negative group delay “channels” offer reduced signal latency as compared to conventional “channels”. The results presented in the thesis can be used to design a new generation of electronic and microwave interconnects with reduced or eliminated signal latency.

The causal relationship between financial development and economic growth is a controversial issue. For developing countries, empirical studies have provided mixed result. This study seeks to empirically explore the relationship and the causal link between financial development and economic growth in two sub-Saharan African countries between 1970 and 2006. The empirical investigation is carried out using time methods and the five most commonly used indicators of financial development in the literature. However, the causal relationship was carried out using two different methods which are the autoregressive distributed lag bounds testing (ARDL) and the vector error correction model (VECM). Using this above methodology the study first found that in both countries there is a positive and long-term relationship between all the indicators of financial development and economic growth which was proxied by the real per capita GDP. With respect to the causality test, the two methods used provide mixed results especially in South Africa. In Cameroon the study found that financial development causes economic growth using the two methods, whereas in South Africa economic growth causes financial development when the VECM method is used, while there is an independence relationship between the two variables in South Africa when using ARDL. / Economics / M.Comm. (Economics)

We consider a number of temporal logics, some interval-based and some instant-based, and the choices that have to be made if we need to construct a computational framework for such a logic. We consider the axiomatisation of the accessibility relations of the underlying temporal structures when we are using a modal language as well as the formulation of axioms for distinguishing concepts like actions, events, processes and so on for systems using first-order languages. Finally, we briefly discuss the fields of application of temporal logics and list a number of fields that looks promising for further research. / Computer Science & Information Systems / M.Sc.(Computer Science)