Testing Substitutability of Weak Preferences

In many-to-many matching models, substitutable preferences constitute the largest domain for which a pairwise stable matching is guaranteed to exist. In this note, we extend the recently proposed algorithm of Hatfield et al. [3] to test substitutability of weak preferences. Interestingly, the algorithm is faster than the algorithm of Hatfield et al. by a linear factor on the domain of strict preferences.Comment: 7 page

Testing Top Monotonicity

Top monotonicity is a relaxation of various well-known domain restrictions such as single-peaked and single-crossing for which negative impossibility results are circumvented and for which the median-voter theorem still holds. We examine the problem of testing top monotonicity and present a characterization of top monotonicity with respect to non-betweenness constraints. We then extend the definition of top monotonicity to partial orders and show that testing top monotonicity of partial orders is NP-complete

When can school inputs improve test scores?

The relationship between school inputs and educational outcomes is critical for educational policy. The authors recognize that households will respond optimally to changes in school inputs and study how such responses affect the link between school inputs and cognitive achievement. To incorporate the forward-looking behavior of households, the authors present a household optimization model relating household resources and cognitive achievement to school inputs. In this framework, if household and school inputs are technical substitutes in the production function for cognitive achievement, the impact of unanticipated inputs is larger than that of anticipated inputs. The authors test the predictions of the model for nonsalary cash grants to schools using a unique data set from Zambia. They find that household educational expenditures and school cash grants are substitutes with a coefficient of elasticity between -0.35 and -0.52. Consistent with the optimization model, anticipated funds have no impact on cognitive achievement, but unanticipated funds lead to significant improvements in learning. This methodology has important implications for educational research and policy.Housing&Human Habitats,Environmental Economics&Policies,Teaching and Learning,Economic Theory&Research,Economic Conditions and Volatility,Economics of Education

When Can School Inputs Improve Test Scores?

Most studies fail to find an impact of school inputs on outcomes such as test scores. We argue that this might be a consequence of ignoring the possibility that households respond optimally to changes in school inputs and thus obscure the real effect of such provision on cognitive achievement. To incorporate the forward-looking behaviour of households, we present a household optimization model relating household resources and cognitive achievement to school inputs. In this framework if household and school inputs are technical substitutes in the production function for cognitive achievement, the impact of unanticipated inputs is larger than that of anticipated inputs. We test the predictions of the model for non-salary cash grants to schools using a unique data set from Zambia. We find that household educational expenditures and school cash grants are substitutes with a coeffcient of elasticity between -0.35 and -0.52. Consistent with the optimization model, anticipated funds have no impact on cognitive achievement, but unanticipated funds lead to significant improvements in learning. We are thus able both to order the effects of different kinds of spending and capture their impact on cognitive achievement.

Complexity of stability in trading networks

Efficient computability is an important property of solution concepts. We consider the computational complexity of finding and verifying various solution concepts in trading networks—multi-sided matching markets with bilateral contracts and without transferable utility—under the assumption of full substitutability of agents’ preferences. It is known that outcomes that satisfy trail stability always exist and can be found in linear time. However, we show that the existence of stable outcomes—immune to deviations by arbitrary sets of agents—is an NP -hard problem in trading networks. We also show that even verifying whether a given outcome is stable is NP -hard in trading networks

Trade, Poverty and Inequality: Evidence from the End of the Multifiber Arrangement in India

Does free and fair trade benefit the workers in an industry? My thesis investigates this question in the context of the Multifiber Arrangement, a system of quotas established in 1974 to protect the textile industries in developed countries by restricting cheaper imports from developing countries. Lifting of these quotas mandated by the WTO between 1995 and 2005, therefore, meant opportunities for greater textile production in internationally competitive developing economies such as India, where the textile industry accounts for over 5.2% of global production and is the second largest generator of employment after agriculture. In labor-intensive industries, an increase in production should further mean more employment, and possibly higher wages and improved livelihood. Using variation in the pre-agreement industry mix across states in India, my results suggest that textile and clothing production and employment grew as the MFA quotas were lifted, and that larger textile-producing states pre-reform saw a greater increase in output and employment than smaller producers. I also find that larger producers of textiles experienced a greater decline in absolute poverty, but a differential rise in inequality; benefits to the quota removal seem to be going to the owners of big textiles businesses, and not workers

Complementarities and Substitutabilities Among Knowledge Sourcing Strategies and Their Impact on Firm Performance

Knowledge sourcing strategy (KSS) is regarded as a key determinant of successful Knowledge Management (KM). However, prior research on how KSSs can improve firm performance has produced inconsistent results. This may be due to inadequate consideration of complementary and substitutable relationships in KSSs. Whereas previous studies have assessed the impact of individual KSS on firm performance, in practice firms adopt several different KSSs simultaneously. Drawing on the Knowledge-based View (KBV) and the complementarity theory, this study investigates the impact of multiple KSSs, in terms of sourcing type and origin, to develop three sets of hypotheses on complementarity and substitutability. Survey data collected from 372 firms in Korea are analyzed to test the hypotheses using the supermodularity and submodularity functions. The results confirm complementary relationships between system- and external-oriented, between person- and internal-oriented, and among system-, person-, and internal-oriented strategies, as well as substitutable relationships between person- and external-oriented strategies. Interestingly, different knowledge sourcing patterns between knowledge intensive and non-knowledge intensive environments are revealed. This study expands KM research by developing a new conceptual framework of KSSs and employing advanced analytical approaches to explore the relationships between KSSs and firm performance. It also offers valuable practical suggestions for managers in selecting successful combinations of KSSs using a judicious combination of system- and external-oriented, of person- and internal-oriented, or of system-, person-, and internal-oriented strategies

Automata and linear temporal logic : translations with transition-based acceptance

Automata theory provides powerful tools for designing and implementing decision procedures for temporal logics and their applications to the automatic verification of systems against their logical specifications. Implementing these decision procedures by making use of automata built from the systems and their specifications with translation procedures is challenging in practice due to the tendency of the automata to grow easily unmanageably large as the size of the systems or the logical specifications increases. This thesis develops the theory of translating propositional linear time temporal logic (LTL) into nondeterministic automata via self-loop alternating automata. Unlike nondeterministic automata, self-loop alternating automata are expressively equivalent to LTL and allow a conceptually simple translation of LTL specifications into automata using a set of rules for building automata incrementally from smaller components. The use of generalized transition-based acceptance for automata throughout all constructions gives rise to new optimized translation rules and facilitates designing heuristics for the minimization of automata by making use of language containment tests combined with structural analysis of automata. The generalized definition also supports the translation of self-loop alternating automata into nondeterministic automata by essentially applying the standard subset construction; this construction can be further simplified and optimized when working with automata built from LTL formulas. The translation rules can also be used to identify a syntactic subclass of LTL for which the exponential increase caused by the subset construction in the number of states of the automaton can always be avoided; consequently, the satisfiability problem for this subclass, which is shown to extend related subclasses known from the literature, is NP-complete. Additionally, the emptiness of generalized nondeterministic automata is shown to be testable without giving up generalized transition-based acceptance by using a new variant of the well-known nested depth-first search algorithm with improved worst-case resource requirements.Automaattiteorian avulla voidaan suunnitella ja toteuttaa temporaalilogiikkojen ratkaisumenetelmiä sekä näiden menetelmien sovellutuksia logiikoilla järjestelmistä esitettyjen oikeellisuusvaatimusten tietokoneavusteiseen verifiointiin. Käytännössä näiden ratkaisumenetelmien toteuttaminen kääntämällä järjestelmät ja niiden oikeellisuusvaatimukset automaateiksi on kuitenkin haasteellista, sillä näistä automaateista tulee järjestelmien tai loogisten vaatimusten koon kasvaessa helposti niin suuria, ettei niitä enää voida käsitellä. Tässä väitöskirjassa kehitetään lineaarisen ajan temporaalilogiikan (LTL) epädeterministisiksi automaateiksi kääntämisen teoriaa käyttämällä käännöksen apuna vain yhden tilan silmukoita sisältäviä alternoivia automaatteja, joilla – toisin kuin epädeterministisillä automaateilla – on sama ilmaisuvoima kuin lineaarisen ajan temporaalilogiikalla. Tätä logiikkaa voidaan kääntää näiksi automaateiksi soveltaen yksinkertaisia sääntöjä automaattien yhdistämiseksi vaiheittain keskenään yhä suuremmiksi automaateiksi. Käyttämällä yleistettyä siirtymäpohjaista hyväksyvyyden määritelmää automaateille kaikissa käännöksen vaiheissa voidaan näin muodostettuja automaatteja sieventää uusin tavoin käyttäen apuna automaattien hyväksymien kielten välisiä sisältyvyyssuhteita sekä automaattien rakenteellisia ominaisuuksia. Yleistetyn määritelmän ansiosta vain yhden tilan silmukoita sisältävät alternoivat automaatit voidaan myös kääntää edelleen epädeterministisiksi automaateiksi soveltamalla yleisesti tunnettua osajoukkokonstruktiota lähes sellaisenaan. Tämä konstruktio voidaan edelleen tehdä yksinkertaisemmin ja tehokkaammin LTL-kaavoista muodostetuille automaateille. Automaattikäännöksessä käytettävien sääntöjen avulla voidaan myös erottaa lineaarisen ajan temporaalilogiikan syntaktinen osajoukko, jonka kaavat onmahdollista kääntää epädeterministisiksi automaateiksi ilman, että automaattien tilojen määrä kasvaa osajoukkokonstruktion tavoin eksponentiaalisesti. Tästä tuloksesta seuraa, että kyseisen LTL:n osajoukon toteutuvuusongelma on NP-täydellinen. Osajoukko on samankaltaisia kirjallisuudessa aiemmin esiteltyjä osajoukkoja aidosti laajempi. Väitöskirjassa esitetään myös, kuinka epädeterministisen automaatin hyväksymän kielen tyhjyys voidaan tarkastaa luopumatta yleistetystä siirtymäpohjaisesta hyväksyvyyden määritelmästä käyttäen algoritmia, joka on uusi, huonoimman tapauksen vaatimuksiltaan tehokkaampi muunnos tunnetusta sisäkkäisestä syvyyshakualgoritmista.reviewe