Using Taylor Rule to Explain Effects of Institutional Changes in Central Banks

In this paper we trace changes in monetary policy caused by institutional amendments in legal acts of central banks. We estimate coefficients of the Taylor Rule for central banks of Sweden, United Kingdom, Switzerland and EU15 to shed some light on monetary policy ex ante and ex post significant improvements in central bank independence. Results presented suggest differences in accommodating monetary policy in countries and support the idea that initial level of CBI matters for reactions to variability both of inflation and output gap. A preindependence period characterizes with strong inflation targeting features, whereas a post-independence time resembles more discretionary type of monetary policy. As a spin-off from our original idea, we find that changing properties of inflation in the last decade make econometric analysis more difficultTaylor rule, central bank independence, interest rate rules

Quest for the Best: How to Measure Central Bank Independence and Show its Relationship with Inflation

The objective of this paper is to check measures for explanatory power of central bank independence (CBI) in a series of econometric tests. Measures of central bank autonomy offer a useful expression of the extent to which a central bank is able to keep the government away from influencing a change in the inflation rate. The more a measure represents this idea, the easier one can find a relation between the CBI value and the inflation rate. Results of estimations show that proxies by Grilli et al. (1991) are strong regressors of inflation rate, contrary to those by Cukierman et al. (1992). Moreover, estimation results challenge the belief that divergences in CBI-inflation rate estimations are due to differences in institutional features across samples of countries, not to differences in legal proxies of central bank independence. Already results from a homogenous group of industrial countries indicate that some indices perform “better” than others.Central bank independence, political autonomy, economic autonomy, institution, estimation

Quest for the best: How to measure central bank independence and show its relation with inflation?

We use several numerical tests in order to receive answers to our three questions. First, this paper aims to indicate, which measure of central bank independence explains economic changes the most accurately, and hence gives the most exact guidance onto institutional design of monetary authorities. Second, our aim is to prove that differences in legal proxies matter as much as institutional development of countries. Finally, we show that results are vulnerable to data modification. This experiment is performed by an empirical verification of the quality of CBI indices, comparing several widely used measures for around 100 countries, using a panel data approach. After a brief description of imprecision in CBI measures methodology and their definitions, a comparison using OLS method is made. Additional tests of TSLS, PCA and stepwise selection are used, as well. In the final conclusion we are able to point the ``winner'' of this experiment but also we indicate that a minor modification of data can change the result.institution, central bank independence, panel data

Audience-Centric Natural Language Generation via Style Infusion

Adopting contextually appropriate, audience-tailored linguistic styles is critical to the success of user-centric language generation systems (e.g., chatbots, computer-aided writing, dialog systems). While existing approaches demonstrate textual style transfer with large volumes of parallel or non-parallel data, we argue that grounding style on audience-independent external factors is innately limiting for two reasons. First, it is difficult to collect large volumes of audience-specific stylistic data. Second, some stylistic objectives (e.g., persuasiveness, memorability, empathy) are hard to define without audience feedback. In this paper, we propose the novel task of style infusion - infusing the stylistic preferences of audiences in pretrained language generation models. Since humans are better at pairwise comparisons than direct scoring - i.e., is Sample-A more persuasive/polite/empathic than Sample-B - we leverage limited pairwise human judgments to bootstrap a style analysis model and augment our seed set of judgments. We then infuse the learned textual style in a GPT-2 based text generator while balancing fluency and style adoption. With quantitative and qualitative assessments, we show that our infusion approach can generate compelling stylized examples with generic text prompts. The code and data are accessible at https://github.com/CrowdDynamicsLab/StyleInfusion.Comment: 14 pages, 3 figures, Accepted in Findings of EMNLP 202

Creating, Metavoicing, and Propagating: A Road Map for Understanding User Roles in Computational Advertising

Over the past two decades, everyday users have become a prominent force in the advertising landscape. They actively participate in conversations with and about brands by creating, amplifying, and interacting with brand-related messages. These user activities generate large volumes of structured and unstructured data that advertisers can mine to understand consumer interests and preferences. In this article, we survey insights from the user-generated content literature through the computational advertising lens to offer a road map for future research. Specifically, we discuss three roles that users play—as creators, metavoicers, and propagators. For each role, we present key research areas that can benefit from a computational approach, identify the opportunities and challenges, and propose questions for future research. We also discuss the practical implications of applying computational methods to study users and user-generated content for advertisers

Dynamics between social media engagement, firm-generated content, and live and time-shifted TV viewing

Purpose The purpose of this paper is to study consumer engagement as a dynamic, iterative process in the context of TV shows. A theoretical framework involving the central constructs of brand actions, customer engagement behaviors (CEBs), and consumption is proposed. Brand actions of TV shows include advertising and firm-generated content (FGC) on social media. CEBs include volume, sentiment, and richness of user-generated content (UGC) on social media. Consumption comprises live and time-shifted TV viewing. Design/methodology/approach The authors study 31 new TV shows introduced in 2015. Consistent with the ecosystem framework, a simultaneous system of equations approach is adopted to analyze data from a US Cable TV provider, Kantar Media, and Twitter. Findings The findings show that advertising efforts initiated by the TV show have a positive effect on time-shifted viewing, but a negative effect on live viewing; tweets posted by the TV show (FGC) have a negative effect on time-shifted viewing, but no effect on live viewing; and negative sentiment from tweets posted by viewers (UGC) reduces time-shifted viewing, but increases live viewing. Originality/value Content creators and TV networks are faced with the daunting challenge of retaining their audiences in a media-fragmented world. Whereas most studies on engagement have focused on static firm-customer relationships, this study examines engagement from a dynamic, multi-agent perspective by studying interrelationships among brand actions, CEBs, and consumption over time. Accordingly, this study can help brands to quantify the effectiveness of their engagement efforts in terms of encouraging CEBs and eliciting specific TV consumption behaviors