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This article focuses on potential economic implications of a free trade agreement (FTA) between the European Union (EU) and the Indian Federation. The economic implications are evaluated by estimating an Extended gravity model for all existing FTAs with the Indian Federation. Moreover, we control for the trade contribution of EU member countries in our econometric model during the period from 1990 until 2008. The results show a significant increase in trade, if there is a free trade agreement between India and another country. Interestingly, we find that India has the largest positive impact from FTAs with more advanced economies. Thus, we reaffirm the potential benefits of trade relationships between the EU and India.
This paper examines the relationship of asset Price determination via Google data. To capture this relation, I create a model and estimate several time series’ regressions. I use weekly data from 2004 to 2010 from 30 international banks. To my knowledge this is the first study which differentiates between Google’s search volume and Google’s search clicks. I show that asset prices are positively related to the rate of change in Google’s search volume, trading volume and the level of Google search clicks. Secondly, I demonstrate that the absolute level of Google’s search volume and Google’s search clicks
behave differently regarding the asset price dynamics. Google’s search volume, which measures long-run searches, is negatively related while Google’s search clicks have a positive relationship to asset prices. Hence, Google’s data offer new insights on both measuring attention and pricing financial assets.
This paper develops a new governance scheme for a stable and lasting European Monetary Union (EMU). I demonstrate that existing economic governance is based on flawed incentives especially due to insufficient macroeconomic coordination, failures of institutional enforcement and animal spirit in financial markets. All this caused the European sovereign debt crisis in 2010. Consequently, the EMU crisis is not a conundrum at all rather a failure of national and supranational governance. To tackle this problem, I propose a return to flexible but compulsory rules driven by market forces. The new governance principles shall promote the compliance and effective enforcement of rules.
Applied mathematical theory for monetary-fiscal interaction in a supranational monetary union
(2014)
I utilize a differentiable dynamical system á la Lotka-Voletrra and explain monetary and fiscal interaction in a supranational monetary union. The paper demonstrates an applied mathematical approach that provides useful insights about the interaction mechanisms in theoretical economics in general and a monetary union in particular. I find that a common central bank is necessary but not sufficient to tackle the new interaction problems in a supranational monetary union, such as the free-riding behaviour of fiscal policies. Moreover, I show that upranational institutions, rules or laws are essential to mitigate violations of decentralized fiscal policies.
This paper studies the impact of financial liquidity on the macro-economy. We extend a classic macroeconomic modeland compute numerical simulations. The model confirms that persistently low inflation can occur despite a high degreeof financial liquidity due to a reallocation of cash, normal and risk-free bonds. In that regard, our model uncovers anexplanation of a flat Phillips curve. Overall, our approach contributes to a rather disregarded matter in macroeconomictheory.
This article studies the current debate on Coronabonds and the idea of European public debt in the aftermath of the Corona pandemic. According to the EU-Treaty economic and fiscal policy remains in the sovereignty of Member States. Therefore, joint European debt instruments are risky and trigger moral hazard and free-riding in the Eurozone. We exhibit that a mixture of the principle of liability and control impairs the present fiscal architecture and destabilizes the Eurozone. We recommend that Member States ought to utilize either the existing fiscal architecture available or establish a political union with full sovereignty in Europe. This policy conclusion is supported by the PSPP-judgement of the Federal Constitutional Court of Germany on 5 May 2020. This ruling initiated a lively debate about the future of the Eurozone and Europe in general.
Since Adam Smith, the “homo oeconomicus” is the behavioural model in economics. Commonly this model characterizes a selfish individual, a kind of ruthless type, whose greed for profit seems to take precedence over moral values. Already 100 years ago, Max Weber provided a modernization of the model concerning the methodological individualism. Recent research in cognitive sciences reveals a further modernization of this standard model in economics. Neuro-economics, a highly interdisciplinary research field, is building a new behavioural consensus. This article examines the new properties of the “neuro-homo oeconomicus”. We show that the new behavioural model is rather similar to the long-standing economic prototype. To that extent, the neuro-model is more hype than hope. In principle, this article considers an ancient philosophical question about the nature of humans in general.
This paper develops a new methodology in order to study the role of dynamic expectations. Neither reference-point theories nor feedback models are sufficient to describe human expectations in a dynamic market environment. We use an interdisciplinary approach and demonstrate that expectations of non-learning agents are time-invariant and isotropic. On the contrary, learning enhances expectations. We uncover the “yardstick of expectations” in order to assess the impact of market developments on expectations. For the first time in the literature, we reveal new insights about the motion of dynamic expectations. Finally, the model is suitable for an AI approach and has major implications on the behaviour of market participants.
This paper studies option pricing based on a reverse engineering (RE) approach. We utilize artificial intelligence in order to numerically compute the prices of options. The data consist of more than 5000 call- and put-options from the German stock market. First, we find that option pricing under reverse engineering obtains a smaller root mean square error to market prices. Second, we show that the reverse engineering model is reliant on training data. In general, the novel idea of reverse engineering is a rewarding direction for future research. It circumvents the limitations of finance theory, among others strong assumptions and numerical approximations under the Black–Scholes model.