Institutions and Economic Growth of Landlocked Nations – part of dissertation

The study tries to scratch the relationship between institutions and economic growth under the landlocked constraint through empirically growing correlated random effect model with the base of pooled ordinary least square model and supporting models of fixed and random effect model. It includes a balance panel of 134 nations for 16 periods (2144 observations). It concludes that both landlocked and institutions are important variables to increase the output of the country. Landlocked nation decreases economic growth by 36% than no-landlocked nations, but the estimation of remoteness from the center to nearest sea becomes insignificance. Similarly, one standard deviation increase in nine institutional variables individually, out of the seventeen variables, estimates ranges from 3%-9% increase in a standard deviation of the dependent variable gross domestic product per capita.info:eu-repo/semantics/publishedVersio

Institutions, geography and economic prosperity : the case of landlocked countries

Doutoramento em Estudos de DesenvolvimentoThis study engages with, and contributes to, the debate around the determinants of economic growth and prosperity, with special reference to the case of landlocked developing countries. Two main lines of explanation are confronted, summed up by the headings ‘geography’ – landlocked countries are poorer because of the geographical constraints to their participation in international trade – and ‘institutions’ – landlocked countries are poorer because they happen to have worse economic and political institutions, not because of landlockedness per se. The study adopts a cross-country empirical approach combining two main methods, both of which draw on institutional data from the Center for Systemic Peace, Freedom House, The Heritage Foundation and World Governance Indicators. In the first part of the empirical analysis, a comparative descriptive examination is undertaken of the political and economic institutions in various regional groups of landlocked countries. This confirms the hypothesis that European landlocked nations have better economic and political institutions than non- European landlocked countries, but also finds that several institutional variables are non- significantly or even significantly but negatively associated with GDP per capita across the various regional groups of landlocked countries. The second part of the empirical analysis adopts an econometric panel data approach, including a series of alternative models (namely Pooled Least Squares, Fixed Effects, Random Effects and Correlated Random Effects Models) and different specifications, to look at the impact of seventeen institutional variables, in interaction with alternative proxies for landlockedness, upon the (log) level of GDP per capita. We find that several institutional variables are significant predictors of the level of prosperity, but others are non-significant and others still are significantly but negatively associated with GDP per capita. By contrast, landlockedness appears as a powerful predictor of the income level even after controlling for the effect of institutions. We conclude that institutions probably do matter for economic growth and long-term prosperity, but some institutions probably have more complicated and complex relationships with growth than usually assumed, and the question of which institutions to consider and how to properly assess and measure them is not straightforward. Landlockedness, by contrast, seems to be an unequivocal obstacle to economic prosperity.Esta tese situa-se e procura contribuir para o debate em torno dos determinantes do crescimento económico e da prosperidade das economias no longo prazo, com especial referência ao caso dos países em desenvolvimento sem litoral (“landlocked”). São exploradas e confrontadas duas explicações principais para as dificuldades destes países, as quais dão prioridade respetivamente à ‘geografia’ – a ideia de que os países sem litoral são mais pobres devido aos constrangimentos geográficos à sua participação no comércio internacional – e às ‘instituições’ – os países sem litoral são mais pobres porque se dá o caso de terem instituições económicas e políticas piores e não devido ao facto de não terem acesso ao mar. A análise efetuada baseia-se numa abordagem empírica que combina dois conjuntos principais de métodos, ambos os quais assentam em dados institucionais produzidos pelo Center for Systemic Peace, Freedom House, The Heritage Foundation e World Governance Indicators. Na primeira parte da análise empírica, é levada a cabo uma análise comparativa- descritiva das instituições económicas e políticas de diferentes grupos macroregionais de países sem litoral. Esta análise corrobora a hipótese de que os países sem litoral europeus possuem instituições políticas e económicas superiores aos países sem litoral não-europeus, mas conclui também que diversas variáveis institucionais possuem associações não significativas, ou significativas mas negativas, com o PIB per capita em diferentes grupos macroregionais de países sem litoral. A segunda parte da análise empírica é de caráter econométrico, adotando um conjunto de modelos distintos (Pooled Least Squares, Fixed Effects, Random Effects e Correlated Random Effects) e diferentes especificações a fim de estimar o impacto de dezassete variáveis institucionais, em interação com diferentes variáveis proxy representativas da ausência de litoral, sobre o nível (em logaritmo) do PIB per capita. Conclui-se que algumas variáveis institucionais constituem preditores significativos do nível de prosperidade económica, mas algumas outras são não-significativas e outras ainda têm associações significativas mas negativas com a variável dependente. Em contrapartida, a ausência de litoral constitui um preditor significativo e robusto do nível de rendimento per capita mesmo após consideração do efeito das instituições. Conclui-se que, de uma forma geral, as instituições são provavelmente determinantes importantes do crescimento económico e da prosperidade de longo prazo, mas também que algumas instituições mantêm provavelmente relações mais subtis e complexas com o crescimento económico do que é habitualmente considerado, para além de que a escolha de quais as instituições que devem ser consideradas e de qual a forma adequada de medilas coloca os seus próprios desafios. A ausência de litoral, em contrapartida, parece constituir um obstáculo inequívoco à prosperidade económica.info:eu-repo/semantics/publishedVersio

Quantitative empirical trends in technical performance

Technological improvement trends such as Moore’s law and experience curves have been widely used to understand how technologies change over time and to forecast the future through extrapolation. Such studies can also potentially provide a deeper understanding of R&D management and strategic issues associated with technical change. However, this requires that methodological approaches for these analyses be addressed and compared to more effectively interpret results. Our analysis of methodological issues recommends less ambiguous approaches to: 1) the unit of analysis; 2) choice of the metrics within a unit of analysis; 3) the relationships among possible independent variables; and 4) qualitative and quantitative data quality considerations. The paper then uses this methodology to analyze performance trends for 28 technological domains with the following findings: 1. Sahal’s relationship is tested for several effort variables (for patents and revenue in addition to cumulative production where it was first developed). 2. The relationship is quite accurate when all three relationships, ( a. an exponential between performance and time, b. an exponential of effort and time and c. a power law between performance and the effort variable) have good data fits (r2 >0.7) . 3. The power law and effort exponents determined are dependent upon the choice of effort variable but the time dependence exponential is not. 4. In domains where the quantity of patents do not increase exponentially with time, Sahal’s relationship gives poor estimates even though Moore’s law is followed even for these domains. 5. Good data quality for any of the relationships depends upon adequate screening involving not only r2 but also the confidence interval based upon two different statistical tests; by these measures, all 28 domains have high quality fits between the log of performance and time whereas less than ½ show this level of quality for power law fits with patents as the effort variable. Overall, the results are interpreted as indicating that Moore’s law is a better description of longer-term technological change when the performance data come from various designs whereas experience curves may be more relevant when a singular design in a given factory is considered

Modeling technical performance change using design fundamentals

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2016.Cataloged from PDF version of thesis.Includes bibliographical references (pages 193-204).Technical performance improvement exhibits exponential trends, but the rates of improvement for the 28 selected technological domains vary from 3 to 65%. Why does performance improve exponentially? Why do the improvement rates vary widely across the domains? This thesis presents a simple theoretical model that provides an explanatory foundation based on two sets of well-known design fundamentals. The first set conceptualizes inventions arising through combinatorial analogical transfer where new operating ideas are created by combining operating ideas from an existing pool of ideas. This inventive process proceeds on a cumulative basis over time and is perpetuated by injection of basic operating ideas through synergistic exchange between science and technology. The combinatorial analogical transfer coupled with exchange between science and technology naturally leads to exponential behavior. These operating ideas are then embedded in domain artifacts to improve technical performance. Interactions in artifacts and scaling of design variables - two domain specific effects from the second set of design fundamentals- modulate this process. Interactions in artifacts influence the ability of the domains to successfully assimilate the operating ideas. Assimilated ideas change design variables in the artifacts to improve their performance. The relative performance improvement depends on the scaling of design variables of the artifacts. Together these two domain parameters can potentially yield a wide variation in performance improvement rates. According to the model, higher domain interaction parameters retard, whereas higher scaling parameters accelerate, performance improvement rates. The model is shown to be consistent with what is known in the technical change literature. An empirical study tests the model's prediction that higher domain interactions retard performance improvement rates of technological domains. A method for extracting domain interactions using a keyword-based text-mining approach on patents is presented. High normalized counts of keywords representing domain interactions are found to be negatively correlated with low performance improvement rates, thus supporting the model positively. The thesis also presents an independent case study on performance improvement of permanent magnetic materials, and tests two regression models, which predict improvement rates using patent data. Performance of magnetic materials follows an exponential, but halting, improvement trend, and predicted rates from the regression models are consistent with prior result for the 28 technological domains.by Subarna Basnet.Ph. D

Technological Improvement Rates and Evolution of Energy-Based Therapeutics

This paper examines the field of energy-based medical therapies based on the analysis of patents. We define the field as the use of external stimuli to achieve biomedical modifications to treat disease and to increase health. Based upon distinct sets of patents, the field is subdivided into sub-domains for each energy category used to achieve the stimulation: electrical, magnetic, microwave, ultrasound, and optical. Previously developed techniques are used to retrieve the relevant patents for each of the stimulation modes and to determine main paths along the trajectory followed by each sub-domain. The patent sets are analyzed to determine key assignees, number of patents, and dates of emergence of the sub-domains. The sub-domains are found to be largely independent as to patent assignees. Electrical and magnetic stimulation patents emerged earliest in the 1970s and microwave most recently around 1990. The annual rate of improvement of all sub-domains (12–85%) is found to be significantly higher than one we find for an aggregate pharmaceutical domain (5%). Overall, the results suggest an increasingly important role for energy-based therapies in the future of medicine

Artifact interactions retard technological improvement: An empirical study

<div><p>Empirical research has shown performance improvement of many different technological domains occurs exponentially but with widely varying improvement rates. What causes some technologies to improve faster than others do? Previous quantitative modeling research has identified artifact interactions, where a design change in one component influences others, as an important determinant of improvement rates. The models predict that improvement rate for a domain is proportional to the inverse of the domain’s interaction parameter. However, no empirical research has previously studied and tested the dependence of improvement rates on artifact interactions. A challenge to testing the dependence is that any method for measuring interactions has to be applicable to a wide variety of technologies. Here we propose a novel patent-based method that is both technology domain-agnostic and less costly than alternative methods. We use textual content from patent sets in 27 domains to find the influence of interactions on improvement rates. Qualitative analysis identified six specific keywords that signal artifact interactions. Patent sets from each domain were then examined to determine the total count of these 6 keywords in each domain, giving an estimate of artifact interactions in each domain. It is found that improvement rates are positively correlated with the inverse of the total count of keywords with Pearson correlation coefficient of +0.56 with a p-value of 0.002. The results agree with model predictions, and provide, for the first time, empirical evidence that artifact interactions have a retarding effect on improvement rates of technological domains.</p></div

Scatter plot of K_J (annual improvement rates) and 1/KW (reciprocal of normalized count of keywords for 27 domains.

<p>Improvement rates are positively correlated with Pearson correlation coefficient = +0.56 with p-value = 0.002, and Spearman Rank Order correlation = +0.632 with p-value = 0.001. Note that capacitor and electric power transmission data points overlap, and hence appear as one point. The dashed line shows a linear trend line between K_J and 1/KW.</p