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Following Ang and Piazzesi’s (2003) study, the authors use an affine term structure model to study the relevance of macroeconomic (domestic and foreign) factors for Peru’s sovereign yield curve in the period from November 2005 to December 2015. The paper aims to discuss this issue.

Risk premia are modeled as time-varying and depend on both observable and unobservable factors; and the authors estimate a vector autoregressive model considering no-arbitrage assumptions.

The authors find evidence that macro factors help to improve the fit of the model and explain a substantial amount of variation in bond yields. However, their influence is very sensitive to the specification model. Variance decompositions show that macro factors explain a significant share of the movements at the short and middle segments of the yield curve (up to 50 percent), while unobservable factors are the main drivers for most of the movements at the long end of the yield curve (up to 80 percent). Furthermore, the authors find that international markets are relevant for the determination of the risk premium in the short term. Higher uncertainty in international markets increases bond yields, although this effect vanishes quickly. Finally, the authors find that no-arbitrage restrictions with the incorporation of macro factors improve forecasts.

To the authors’ knowledge this is the first application of this type of models using data from an emerging country such as Peru.

Large or increasing stocks of non-performing loans in the banking sector constitute threats to financial stability. This paper considers to which extent various macroeconomic and macro-financial factors may serve as leading indicators for the dynamics of the ratio of non-performing loans to total loans.

The paper estimates panel data models for all EU countries and two groups of EU countries using quarterly data over approximately 20 years.

The estimations show that many macroeconomic and macro-financial variables are leading indicators for non-performing loans in the EU countries, even years ahead. Higher GDP growth, lower inflation and lower debt are robust leading indicators of a lower ratio of non-performing loans in the future. The current account balance and real house prices are important indicators for the Western European group but not for the Central and Eastern European group.

The estimations are carried out for panels of EU countries and the effects may hence be seen as averages for the countries in the particular panel and may not apply for individual countries.

National and international authorities have brought in systems to detect and address imbalances and emerging problems in the financial sectors. Many of the measures operate with long lags, and so it is important to assess whether various macroeconomic and macro-financial variables may serve as leading indicators for future developments of non-performing loans.

The main contribution of the paper is that it estimates models meant expressly for predicting non-performing loans several years ahead. The results are thus of practical use for national and international authorities which typically have access to measures that operate with a long delay. The analysis also includes more macroeconomic and macro-financial variables as leading indicators than have typically been used in earlier studies.

WordPerfect version 5.0 has been widely praised for its enhancements with programmable macros. Based on a tradition of macro support since version 2.23, WordPerfect 5.0 allows users to manipulate text in ways previously possible only with more advanced programming languages. The new version, for example, allows for the assignment of variables, conditional testing, advanced looping, sub‐routines, and error handling. It also includes a macro editor as part of the basic software package. With the editor, you can easily modify existing macros—a feature particularly useful with large macros created with the new programming features. In this article I will provide a basic introduction to these macro capabilities and their uses. I have also designed a simple accessions list macro (ACCLIST) that demonstrates some of the new features. A later article will illustrate more complex possibilities.

The present study investigates the impact of financial soundness variables on bank performance in emerging countries.

This study uses macro-level panel data from 17 countries from 2011 to 2020. The analysis adopts six models. While four models include bank profitability, the dependent variable of the other models is Bank Z Scores. Regulatory Capital to Risk-Weighted Assets, Liquid Assets to Total Assets, Non-Performing Loans to Total Gross Loans and Non-Interest Expenses to Gross Income are proxies of financial soundness variables.

The authors estimate fixed and random effects models with the Arellano, Froot and Rogers methods. Empirical results show that Non-Performing Loans to Total Gross Loans harm ROA and ROE. Regulatory Capital to Risk-Weighted Assets negatively affects ROE. Non-Interest Expenses to Gross Income on Bank Z Scores have a significant and negative effect. Moreover, Inflation, Foreign Direct Investment and GDP are macroeconomic variables that increase bank profitability.

This study contributes to the literature in different aspects. The first is the model of the study. The authors contribute to the literature regarding the variables used to measure financial soundness. Secondly, emerging countries are samples in the study. A significant part of the studies on financial soundness has focused on developed countries. Finally, the authors analyze the macro-level data. Bank soundness studies mainly investigate country-level variables. Macro-level analysis may provide an advantage in combating global financial crises.

This paper aims to establish the effect of bank regulations on financial stability in Kenya. Specifically, the study seeks to uncover the effect of micro and macro prudential regulations on financial stability and their trade-offs or complementarities.

Using annual time series data over the period 1990–2017, the study uses structural equation model (SEM) estimation technique. This solves the problem of approximating measurement errors, using both latent constructs and indicator constructs.

Study findings reveal that macro and micro prudential regulations are significant drivers of financial stability. Further, prudential regulations are more effective when they complement each other.

This study centers on how bank regulations affect financial stability. Future research could be carried out on the effect of Non-Bank Financial Institutions regulations on financial system stability.

Complementing macro and micro prudential regulation is more effective and efficient in ensuring stability of the financial system other than letting the two policy objectives operate independently.

Regulatory authorities should introduce prudential regulations that would encourage innovations in the banking sector. This ensures easy deposit mobilization that enhances financial inclusion. Prudential regulations that ensure financial stability will be effective when low income earners are included in the financial system.

To the best of the authors’ knowledge, this study is the first to investigate the role of banking regulations on financial stability. This study is also pioneering in the use of SEM estimation technique, in examining how prudential regulations affect financial stability. Previous cross-country studies have focused on macro prudential regulations ignoring the importance of micro prudential regulations.

Standard macro theories have the same analytical structure as their micro counterparts. Where micro theories work with equilibrium between supply and demand for particular products, macro theories work with equilibrium applied to aggregates of products. This common approach treats the micro–macro relationship as scalable, with macro variables being aggregations over micro variables. In contrast, we pursue a systems-theoretic approach to the micro–macro relationship. This relationship is not scalable and rather entails a disjunction between micro- and macro-levels of theory. While micro phenomena are still susceptible to choice-theoretic analysis, macro phenomena are products of ecological interaction and so entail emergent phenomena. Our alternative approach treats macro theory as a form of systems theory where the behavior of the system has properties that are not reducible to properties of the individual elements within that system. Besides sketching this alternative approach, we examine some of the different insights this approach offers into such topics as unemployment and stabilization.

The purpose of this paper is to examine the relationship between unemployment and social participation and aim to identify the role of national policies and attitudes as possible mediators.

The authors use the 2006 EU-SILC module on social participation – a data set that provides rich information on social participation for 22/23 EU countries. They adopt a two-step multi-level design, allowing them to directly examine the impact of national policies and norms on individual outcome.

The paper reveals clear evidence that the unemployed have lower levels of social participation than the employed across a range of indicators. The paper also reveals that macro-level variables significantly affect the extent of these differentials in social participation. For instance, the authors found that societies that expose the unemployed to poverty risk have a larger social participation gap between the employed and the unemployed.

While the negative association between unemployment and social participation has been established in prior work, the study is the first one to employ a “large N” comparison and to use a multi-level design to statistically test the degree to which macro-level variables mediate the negative relationship between unemployment and social participation. The analyses were able to show that societal context can significantly alleviate the negative implications of unemployment for social participation.

The purpose of this paper is to determine if macroeconomic announcements affect the Fama‐French market, size, book‐to‐market risk factors and momentum factor.

Using unexpected announcements of major macroeconomic indicators, a study is made of how daily innovations of risk factors react to macroeconomic shocks. In a Flannery and Protopapadakis framework, the impact of macroeconomics surprises on the levels and volatilities of the risk factors is measured. A VAR model is employed as a robustness check. To better understand the mechanism of announcement impacts on risk factors, the relationship between the macroeconomics announcements and Fama‐French size/book‐to‐market portfolio returns is investigated.

Inflation, employment, consumption and business activities were found to affect levels and volatilities of risk factors. However, these macro variables affect risk factors differently. Inflation and non‐farm payrolls decrease the market risk premium while increasing the size premium. Personal income increases the size premium while reducing the book‐to‐market premium. Industrial production and GDP only influence the level of the momentum factor. In this model specification, producer inflation (PPI) and personal income increase the volatility of the size premium while business inventories increase the volatility of the market premium.

This paper's results support the notion that different risk factors capture different economic fundamentals.