Machine learning for financial transaction classification across companies using character-level word embeddings of text fields

An important initial step in accounting is mapping financial transfers to the corresponding accounts. We devised machine-learning-based systems that automate this process. They use word embeddings with character-level features to process transaction texts. When considering 473 companies independently, our approach achieved an average top-1 accuracy of 80.50%, outperforming baselines that exclude the transaction texts or rely on a lexical bag-of-words text representation. We extended the approach to generalizes across companies and even across different corporate sectors. After standardization of the account structures and careful feature engineering, a single classifier trained on 44 companies from 28 sectors achieved a test accuracy of more than 80%. When trained on 43 companies and tested on the remaining one, the system achieved an average performance of 64.62%. This rate increased to nearly 70% when considering only the largest sector.     

Firm age and performance

Amid increasing interest in firm age and its effects on firm performance, this special issue offers an exhaustive review of the literature and a novel collection of evidence on the effects of firm age on performance, including a special focus of interest on innovation performance, financial performance, exports, survival and growth. This editorial positions the theme in the extant literature, and provides key definitions and challenges ahead in the field of evolutionary economics. It introduces the collection of articles composing the special issue. The papers offer a diversity of country contexts, as well as analytical approaches and methods. They include an exhaustive review of the literature on age and firms’ performance, and present original empirical studies focusing on the effects of age on firms’ economic outcomes on the one hand, and on innovation outcomes on the other hand. While most of the papers use econometric analysis, the level of analysis ranges from firm to individual.     

Bivariate and multivariate scaled association models. An application to homogamy of social origin and education in Hungary between 1930 and 1979

In this article we compare bivariate and multivariate models for homogamy of social origin and education to test whether bivariate models of homogamy lead to biased results. We use data on Hungarian couples married between 1930 and 1979 and loglinear models of scaled association. The results indicate some differences between bivariate and multivariate analyses. At each point of time bivariate models overestimate homogamy, both with respect to education and social origin. However, results on trends in time do not differ much between the two analyses. The exception is the period 1940–1959, in which bivariate analysis showed decreasing educational homogamy, and multivariate analysis showed an increasing trend. The latter finding can be explained by declining homogamy of social origin, as well as the weaker reproduction and cross-effects in this period.     

Road infrastructure and economic development in the periphery: the case of A55 improvements in North Wales

This paper examines the impact of a major road improvement programme on the economic development of North Wales. The paper identifies the economic impacts of the road on a selection of firms and organisations in North Wales, and provides a modelling framework to examine the static and dynamic effects of road improvements. Road improvements across North Wales are found to be a necessary, but not sufficient, condition for economic development in this peripheral area.     

The risk-return trade-off in human capital investment

In this paper, we analyze investments in human capital in a way which is standard for financial assets, but not (yet) for human capital assets. We study mean-variance plots of human capital assets. We compare the properties of human capital returns using a performance measure and by using tests for mean-variance spanning. Fields differ strongly not only in common rates of return, but also in return per unit of risk. We identify a range of educations that are efficient in terms of investment goods, and a range of educations that may be chosen for consumption purposes.     

Killing off cohorts: Forecasting mortality of non-extinct cohorts with the penalized composite link model

Mortality forecasting has crucial implications for insurance and pension policies. A large amount of literature has proposed models to forecast mortality using cross-sectional (period) data instead of longitudinal (cohort) data. As a consequence, decisions are generally based on period life tables and summary measures such as period life expectancy, which reflect hypothetical mortality rather than the mortality actually experienced by a cohort. This study introduces a novel method to forecast cohort mortality and the cohort life expectancy of non-extinct cohorts. The intent is to complete the mortality profile of cohorts born up to 1960. The proposed method is based on the penalized composite link model for ungrouping data. The performance of the method is investigated using cohort mortality data retrieved from the Human Mortality Database for England & Wales, Sweden, and Switzerland for male and female populations.     

Environmental quality indicators: Background,principles and examples from Norway

The need for a simple and general overview of the development in the state of the environment has led to work on environmental indicators in several countries and international organizations. Except for the basic common requirement of providing an overview, the works vary a great deal with regard to final aim, target groups, classification and, hence, choice of indicators. This paper gives an overview of the work carried out in the Central Bureau of Statistics of Norway within this field, with emphasis on the basic principles behind the choice of indicators. A hierarchical system of indicator sets is proposed, and examples of indicators are presented. Also, a brief overview of work carried out elsewhere is included.     

On commodification: volunteer experiences in festivals†

This paper is about the creation of non-commodified volunteer experiences, for tourists and local volunteers participating in festivals. How is the tourist experience created when most of the traditional tourism demands are not fulfilled? And what are the experiences and how do they relate to different ‘regimes of value’? The experience context includes tourists who work together with locals voluntarily in a festival, where the volunteers pay for their own travel, food, overnight stay, and work for free. To gain more knowledge on the volunteers is important because local cultural life becomes more festivalized, most festivals are reliant on the involvement of volunteers, and the festivals gain an important role in an economy where even small places are engaged in branding [Löfgren, O. 2003. The new economy: A cultural history. Global Networks, 3, 239–254]. This paper uses a qualitative approach. Interviews were conducted (n?=?23) and participants were observed during four festivals in Finnmark, Norway. Nothing in the experiences was facilitated, and the experience creation occurred in the work tasks together with volunteer colleagues. It was like a holiday experience, without a stream of commodified moments. It was a value creation that could be seen as authentic and real, created in the interaction between the local and visiting volunteers.