Why economics should be a modest and reasonable science

Unlike the methodological sciences such as mathematics and decision theory, which use the hypothetical-deductive method and may be fully expressed in complex mathematical models because their only truth criterion is logical consistency, the substantive sciences have as their truth criterion the correspondence to reality, adopt an empirical-deductive method, and are supposed to generalize from and often unreliable regularities and tendencies. Given this assumption, it is very difficult for economists to predict economic behavior, particularly major financial crises.

Three Remarks on “Reflective Equilibrium“

John Rawls’ “reflective equilibrium” ranges amongst the most popular conceptions in contemporary ethics when it comes to the basic methodological question of how to justify and trade off different normative positions and attitudes. Even where Rawls’ specific contractualist account is not adhered to, “reflective equilibrium” is readily adopted as the guiding idea of coherentist approaches, seeking moral justification not in a purely deductive or inductive manner, but in some balancing procedure that will eventually procure a stable adjustment of relevant doctrines and standpoints. However, it appears that the widespread use of this idea has led to some considerable deviations from its meaning within Rawls’ original framework and to a critical loss of conceptual cogency as an ethico-hermeneutical tool. This contribution identifies three kinds of “balancing” constellations that are frequently, but inadequately brought forth under the heading of Rawlsian “reflective equilibrium”: balancing theoretical accounts against intuitive convictions; balancing general principles against particular judgements; balancing opposite ethical conceptions or divergent moral statements, respectively. It is argued that each of these applications departs from Rawls’ original construction of “reflective equilibrium” and also deprives the idea of its reliability in clarifying and weighing moral stances

The Two Methods of Economics

A Teoria Econômica Emprega Dois Métodos: o Método Hipotético-Dedutivo, Utilizado Principalmente Pelos Economistas Neoclássicos, e o Método Histórico-Dedutivo, Adotado Pelos Economistas Clássicos e Keynesianos. Ambos são Legítimos, Mas, Desde que a Economia é Substantiva, não uma Ciência Metodológica, Onde o Objeto é o Sistema Econômico, o Método Histórico-Dedutivo é o Mais Apropriado. o Método Hipotético-Dedutivo Permite que o Economista Desenvolva Ferramentas para Analisar o Sistema Econômico, Mas Falha ao Analisar o Sistema como um Todo. em Contrapartida, o Método Histórico-Dedutivo Parte da Observação Empírica da Realidade e da Busca por Regularidades e Tendências. é um Método Empírico, Apropriado para as Ciências Substantivas que Tratam de Sistemas Abertos, como é o Caso da Economia.

Untenable nonstationarity: An assessment of the fitness for purpose of trend tests in hydrology

The detection and attribution of long-term patterns in hydrological time series have been important research topics for decades. A significant portion of the literature regards such patterns as ‘deterministic components’ or ‘trends’ even though the complexity of hydrological systems does not allow easy deterministic explanations and attributions. Consequently, trend estimation techniques have been developed to make and justify statements about tendencies in the historical data, which are often used to predict future events. Testing trend hypothesis on observed time series is widespread in the hydro-meteorological literature mainly due to the interest in detecting consequences of human activities on the hydrological cycle. This analysis usually relies on the application of some null hypothesis significance tests (NHSTs) for slowly-varying and/or abrupt changes, such as Mann-Kendall, Pettitt, or similar, to summary statistics of hydrological time series (e.g., annual averages, maxima, minima, etc.). However, the reliability of this application has seldom been explored in detail. This paper discusses misuse, misinterpretation, and logical flaws of NHST for trends in the analysis of hydrological data from three different points of view: historic-logical, semantic-epistemological, and practical. Based on a review of NHST rationale, and basic statistical definitions of stationarity, nonstationarity, and ergodicity, we show that even if the empirical estimation of trends in hydrological time series is always feasible from a numerical point of view, it is uninformative and does not allow the inference of nonstationarity without assuming a priori additional information on the underlying stochastic process, according to deductive reasoning. This prevents the use of trend NHST outcomes to support nonstationary frequency analysis and modeling. We also show that the correlation structures characterizing hydrological time series might easily be underestimated, further compromising the attempt to draw conclusions about trends spanning the period of records. Moreover, even though adjusting procedures accounting for correlation have been developed, some of them are insufficient or are applied only to some tests, while some others are theoretically flawed but still widely applied. In particular, using 250 unimpacted stream flow time series across the conterminous United States (CONUS), we show that the test results can dramatically change if the sequences of annual values are reproduced starting from daily stream flow records, whose larger sizes enable a more reliable assessment of the correlation structures