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Is Core Inflation a Better Measure than Headline Inflation in Jordan?

Is Core Inflation a Better Measure than Headline Inflation in Jordan?

This illustrates the importance of this study; it is key to know if the monetary authority ought to switch to core inflation rather than headline inflation, or CPI, for setting monetary policy. This study aims to clarify how core inflation can be calculated and connected to macroeconomic variables through monthly data for the period (1994- 2014). For this purpose, an econometric model that fits the nature of the Jordanian economy is applied. Through this model, this research will examine the impact of macroeconomic variables on core inflation and will show the extent to which this index can be relied upon as an alternative index for headline inflation. Specifically, this research will study how core and headline inflation rates are related to a number of economic variables. These economic variables include: broad money supply M2 to represent monetary policy, tax to represent fiscal policy, the index of industrial production to represent economic activity level, and oil prices to represent international price levels.

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Swapping headline for core inflation: an asset liability management approach

Swapping headline for core inflation: an asset liability management approach

Whether inflation indexation should be performed based on core rather than headline inflation benchmarks or on CPI rather than RPI indices has been a core concern for central banks and pension funds, academics and practitioners alike. To this day, most inflation-targeting central banks around the world display headline inflation targets to anchor expectations, and some have even switched from core to headline targeting in the last decade or so in order to have targets that are directly understandable by politicians, financial markets practitioners and the general public: South Korea switched to headline targets in 2007 (Bank of Korea, 2006) and Thailand might follow suit (McCauley, 2007), leaving South Africa’s and Norway’s central banks as the only two displaying explicit core targets out the 23 of them using inflation-targeting. Still, academics used to present core inflation as the most efficient monetary policy target as in (Mishkin & Schmidt-Hebbel, 2007) or (Wynne, 1999). More recent works like (Gregorio, 2012) or (Walsh, 2011) tend to challenge that assumption in light of recent events where food inflation displayed persistency, especially in less advanced countries. But in spite of this tide of evidence pointing towards headline inflation indexation, we defend in this paper the idea that the time may have come to rethink our long-term inflation hedging strategies and move towards a core indexation of long-term inflation liabilities to the greater benefit of those seeking protection from monetary erosion.

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What inflation measure should a currency union target?

What inflation measure should a currency union target?

prices of non-energy consumption-goods adjust downwards gradually. Whether the monetary policymaker targets the headline inflation or the core inflation, the nominal interest rate falls. As a result, the households in the whole union increase expenditure on both energy good and non-energy consumption goods. Both home and foreign non- energy consumption-goods firms produce more outputs to meet the demands. Thus, except for home non-energy consumption-goods firms, which decrease the energy- good input because of technological advance, all other parties increase the demands for the energy good. On the whole, the expansionary demands in the energy-good market push the energy-good price up. Therefore, the decrease in core inflation is greater than the decrease in headline inflation. Upon impact, the CIT policy results in the level of the nominal interest rate being lower than that for the HIT policy.

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Has core inflation been doing a good job in Brazil?

Has core inflation been doing a good job in Brazil?

On practical grounds, despite its increasing use by central banks in recent years – which has been boosted by the adoption of inflation targeting (IT) regimes in several countries – there has been some disenchantment with core inflation. From a policymaker’s perspective, for example, some central banks that used to establish their inflation targets in terms of core inflation (Australia, New Zealand and Czech Republic), have changed their minds and now aim at keeping inflation in line with targets set for headline inflation. In other cases, the targeted indexes, which excluded interest rates effects, have been ruled out in favour of headline inflation (e.g. South Africa and the UK). 3 Moreover, in some countries, such as Canada, where core inflation is used as an operational guide, the “official” core has been replaced by a supposedly better one, showing the dangers of relying too much on any specific core measure. Indeed, if there is a consensus about core inflation today it is that no specific measure dominates others in all dimensions and criteria [see Hogan et al. (2001) for Canada, Mankikar and Paisley (2002) for the U.K, and Rich and Steindel (2007) for the U.S.].

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An evaluation of core inflation measures for Malta

An evaluation of core inflation measures for Malta

The TM measure correlates strongly with the PW measure, which confirms the robustness of these measures and their success in removing the noise from the data and better tracking underlying inflation. These two core inflation indicators are less volatile than headline HICP inflation, resulting in dampened peaks and troughs, especially during the period 2007-2010, in which inflation was particularly volatile. Core inflation can also be considered as the long-term trend in inflation. To this end such a measure, which is an unobservable variable, can be inferred by performing a trend-cycle decomposition of headline inflation using an Unobserved Components Model, a univariate time-series technique given by:

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Understanding the dynamics of inflation volatility in Nigeria: A GARCH perspective

Understanding the dynamics of inflation volatility in Nigeria: A GARCH perspective

variance of the country’s headline CPI series and investigating its impacts on other macro-economic variables. These studies include that of Idowu and Hassan (2010) who explore the relationship between headline inflation uncertainty and economic growth using quarterly headline CPI for the period 1970 to 2007. Also, Udoh and Egwaikhide (2008) use the GARCH model to estimate headline inflation volatility and examined its impacts on foreign direct investment between 1970 and 2005, using annual data. Others include Adamgbe (2003) who fits a symmetric GARCH (1, 1) model to provide volatility estimates for Nigeria’s headline CPI using annual data for the period 1970-2001. These studies assumed symmetric response of inflation volatility to positive and negative shocks as implied by the basic GARCH model. However, such a symmetric restriction in the GARCH model has been rejected by several empirical studies as inflation volatility was found to be more sensitive to positive inflation shocks than to negative shocks (Brunner and Hess, 1993).

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Core Inflation: The Malaysian Case

Core Inflation: The Malaysian Case

Another important fact is that relative to the overall inflation, changes in core inflation are very unlikely to reverse within a short time frame. This suggests that over time headline inflation would revert to core inflation. One could see this from the preceding aggregate supply equation propose by Roger [7] (1998) where short-term deviations would cause headline inflation to move away from core inflation. Over time, once these shocks dissipate headline inflation would converge to core inflation. Various studies have been conducted to test whether the divergence between the headline inflation and core inflation is temporary or otherwise, with mixed results. For instance, Rich and Steindel [9] (2007) find significant reversion of headline CPI inflation to core CPI inflation over 12 quarters from 1978 to 2004. Their earlier work in 2005 using PCE4 price inflation for the 1978-2004 and 1959-2004 periods also yield similar results. Armour [16] (2006) studies the CPI inflation and core inflation for Canada and concludes core inflation measurements do provide unbiased forecast for future headline inflation and are useful indicators although forecast results are not entirely robust. Mankikar and Paisley [15] (2004) run some tests to check for convergence in the UK CPI inflation and core inflation series using a standard method proposed by Marques et al. [17] (2000). They find only three (out of 13) of the measures of core inflation pass all the necessary tests. Finally, a paper by OECD [18] (2005) finds headline inflation tends to revert to core inflation in the United States, Canada and Japan but not in the Euro Area and somewhat ambiguous for the UK.

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Neural Headline Generation on Abstract Meaning Representation

Neural Headline Generation on Abstract Meaning Representation

To answer this research question, this paper pro- poses and evaluates a headline generation method based on an encoder-decoder architecture on Ab- stract Meaning Representation (AMR). The method is essentially an extension of attention-based sum- marization (ABS) (Rush et al., 2015). Our pro- posed method encodes results obtained from an AMR parser by using a modified version of Tree- LSTM encoder (Tai et al., 2015) as additional in- formation of the baseline ABS model. Conceptu- ally, the reason for using AMR for headline gen- eration is that information presented in AMR, such as predicate-argument structures and named entities, can be effective clues when producing shorter sum- maries (headlines) from original longer sentences. We expect that the quality of headlines will improve with this reasonable combination (ABS and AMR). 2 Attention-based summarization (ABS) ABS proposed in Rush et al. (2015) has achieved state-of-the-art performance on the benchmark data of headline generation including the DUC-2004 dataset (Over et al., 2007). Figure 1 illustrates the model structure of ABS. The model predicts a word sequence (summary) based on the combination of the neural network language model and an input sen- tence encoder.

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“President Vows to Cut <Taxes> Hair”: Dataset and Analysis of Creative Text Editing for Humorous Headlines

“President Vows to Cut <Taxes> Hair”: Dataset and Analysis of Creative Text Editing for Humorous Headlines

We specifically studied whether the “setup and punchline” (Rochmawati, 2017) approach is used in funny headline generation, where the humor comes toward the end of the joke after a setup at the beginning. This has been verified numeri- cally for funny cartoon captions by Shahaf et al. (2015). For our analysis, we construct the joke profile graph, shown in Figure 5. It shows the proportion of time the editors substituted a word at each relative word position bin compared to if they randomly chose a word to substitute. Specif- ically, the red curve in the plot shows the propor- tion of replacement word locations if they were chosen randomly from those available in the edit- ing task. The green curve shows the proportion of word locations actually chosen by our editors, and the blue curve shows the difference. We see that the blue line rises monotonically toward the end of the headline, meaning that editors tend to pre- fer replacing words later in the headline. The plot also shows the average funniness grade as a dotted line as a function of the position of the replace- ment word. It rises dramatically toward the end, showing that the funniest headlines were generally those with a replacement word toward the end.

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Low Resource Neural Headline Generation

Low Resource Neural Headline Generation

For ROUGE evaluations, we report ROUGE- 1 and ROUGE-L (Table 2). In contrast with PPL evaluations, some pre-training methods ei- ther don’t improve significantly or even worsen ROUGE measures. Another difference com- pared to PPL evaluations is that for ROUGE, pre- training parameters that reside further from out- puts (embeddings and encoder) seems more ben- eficial. This might imply that a better document representation is more important to stay on topic during beam search while it is less important dur- ing PPL evaluation where predicting next target headline word with high confidence is rewarded and the process is aided by previous target head- line words that are fed to the decoder as inputs. It is also possible, that a well trained decoder be- comes too reliant on expecting correct words as in- puts making it sensitive to errors during generation which would somewhat explain why Enc.+dec. performs worse than Encoder alone. This hypoth- esis can be checked in further work by experiment- ing with methods like scheduled sampling (Bengio et al., 2015) that should increase the robustness to mistakes during generation. Pre-training all pa- rameters on all available text (Enc.+dec.+dist.) still gives the best result on English and quite de- cent results on Estonian. Best models improve ROUGE by 0.85-2.84 points.

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Transforming a Sentence End into News Headline Style

Transforming a Sentence End into News Headline Style

As the most similar work to ours, Sato et al.[6] tries to extract paraphrasing patterns of sentence end by preparing a lot of alignment pairs between news sentences and their headline versions. They compare the sentences from the ends and obtain many correspondences between the two. How- ever, they have no proposals on how to use these one-to-N correspondences, i.e., the way to select one from many candidates. Our approach is to ob- tain many transformation patterns as well, but we do not use aligned corpus; we use a large collec- tion of news headlines instead and find patterns by our thorough observation.

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Growth inflation nexus: threshold model of inflation in India

Growth inflation nexus: threshold model of inflation in India

Raul Ibarra Danilo Trupkin (2011), Wang Zhiyong. (2008). Abis Getachew Makuria (2013), Khan and Senhadji (2001). Sarel (1996), Shamim Ahmed and Md. Golam Mortaza (2005), Cooray (2013), Hayat and Kalirajan, (2009). Munir et al. (2009). Le Thanh Tung and Pham Tien Thanh (2015), Vinayagathasan (2013) Seleteng, Bittencourt and Eyden (2013), Fakhri Hasanov (2011), Stephanie Kremer, Alexander Bick and Dieter Nautz (2011), Samir Ghazouani (2012), David Drukker, Pere Gomis-Porqueras and Paula Hernandez-Verme (2005), Henryk Gurgul and Łukasz Lach (2011), Pypko Sergii (2009), Berber and Artan (2004), Nicas Yabu and Nicholaus J. Kessy (2015) studied that the nexus between economic growth and inflation is positive but there must be threshold level of inflation above which the relationship is negative i.e. inflation above the threshold limit will harm growth. Alvan Ikoku (2015), Costin C. Kiriţescu (2011), Shailender Singh and Amar Singh (2015) Osuala, et al. (2013), Dr. Md. Elias Hossain, Bikash Chandra Ghoshand Md. Khairul Islam (2012), Girijasankar Mallik and Anis Chowdhury (2001), Dr.Kanchan Datta and Dr.Chandan Kumar Mukhopadhyay (2011), verified positive relation between growth and inflation rate. Fikirte Tsegaye Mamo (2012), Md. Shakhaowat Hossin (2013), Muhammad Ayyoub, Imran Sharif Chaudhry and Fatima Farooq (2011), Vikesh Gokal and Subrina Hanif (2004), Ayyoub, Chaudhry, and Farooq (2011), proved in their econometric studies that the nexus between growth and inflation is negative.

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Progress report on the European Union Sustainable Development Strategy 2007. Commission staff working document accompanying the report. SEC (2007) 1416 final, 22 October 2007

Progress report on the European Union Sustainable Development Strategy 2007. Commission staff working document accompanying the report. SEC (2007) 1416 final, 22 October 2007

The sluggish tendencies of environmental tax revenues in many of the EU Member States could be explained by the fact that they might not have been indexed or regularly augmented with inflation and therefore the real value of tax revenues was falling. There may be several reasons for the real value of environmental taxes erosion: first, it may simply be politically difficult to constantly increase the tax rates, in particular, on the products, which affect the energy costs of both households and industry. Secondly, the EU minimum tax rates on mineral oils were kept constant in nominal terms from 1992 until 2004, when the Energy Tax Directive (2003/96/EC) came into force, and did not compel any further increases in national tax rates. In the last few years the strong increases of oil prices may have caused political pressure to lower the tax burden on energy. Increased use of new forms of market-based instruments (that do not generally generate revenue for the general budget) might also be a contributing factor. In particular, the adoption of the EU emissions trading scheme since 2005 leaves less scope for energy taxation and may have been one more reason for the declining share of environmental taxes observed in many Member States in last few years especially as the initial allocation of allowances was not sold or auctioned but awarded for free.

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Automatic Headline Generation using Character Cross Correlation

Automatic Headline Generation using Character Cross Correlation

A window of a length of 10-words was passed over the paragraphs word by word to generate chunks of consecutive words that could be used as headlines. Moving the widow one word step may corrupt the fluency of the sentences. A simple approach to re- duce this issue is to minimize the size of para- graphs. Therefore, the document body was divided into smaller paragraphs at new-line, comma, colon and period characters. This step increased the number of nominated headlines with proper start and end. The resulting is a nominated list of head- lines of a length of 10 words. In the case of a para- graph of a length less than 10, there will be only one nominated headline of the same length of that paragraph.

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Automatic Extraction of News Values from Headline Text

Automatic Extraction of News Values from Headline Text

lent news values and our approach using wikifi- cation proves very reliable. It occurs quite fre- quently – most headlines in The Guardian corpus have at least one entity (median number of entities = 1), which attracts a fair amount of online atten- tion (median Wikipedia long-term prominence = 1,342 pageviews). Some headlines include very prominent entities (max. Wikipedia day-before prominence = 1,031,722). The outputs from New York Times are similar – every headline is asso- ciated with at least one Wikipedia entity (100% prevalence for number of entities); and Wikipedia burstiness, long-term, and day-before prominence have non-zero scores in 66% of headlines. This shows that Wikipedia provides a wide coverage for the computation of prominence. Wikipedia current burst size is a rare feature (12% in The Guardian and 10% in NYT), because capturing an entity in a burst is uncommon, since bursts do not apply to all entities and do not happen frequently.

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Machine Learning Approach to Augmenting News Headline Generation

Machine Learning Approach to Augmenting News Headline Generation

The results of our experiment have shown the TFTrim system (the simplest of the three Topiary-style headline generators examined in this paper) is the most appropriate headline approach because it yields high quality short summaries and, unlike the Topiary and HybridTrim systems, it requires no prior training. This is an interesting result as it shows that a simple tf weighting scheme can produce as good, if not better, topic descriptors than the statistical UTD method employed by the University of Maryland and our own statistical/linguistic approach to topic label identification.

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Diversity of Pythium spp. associated with soybean damping-off, and management implications by using foliar fungicides as seed treatments

Diversity of Pythium spp. associated with soybean damping-off, and management implications by using foliar fungicides as seed treatments

Yields in plots treated with Endura, Evito, Headline and Sercadis were not significantly different over the un- treated control, but certainly these treatments had direct effects in significantly reducing damping off incidence as well as on plant physiology which may have enhanced yield from 0.15 mt/ha in Evito to 0.21 mt/ha in Sercadis treated plots compared with the untreated control (Table 3). On the contrary, plots treated with Aproach and Stratego YLD showed no significant im- pact on damping off incidence, but certainly showed yield advantage of 0.31 mt/ha and 0.26 mt/ha respect- ively over the untreated control (Table 3). Signifi- cantly, the lowest damping off incidence was observed in Priaxor treated plots but yields were 0.03 mt/ha less than the Aproach. Percent incidence of Pythium damping-off in Aproach treated plots was highest among the fungicides tested plots (0.14% less than the untreated plots), but the yield advantage was also highest among the fungicides tested (Table 3), sug- gesting that Aproach fungicide may not have direct effect on Pythium but of plant performance (Table 3). There are reports of Pythium developing resistance or showing insensitivity to products with an active ingredi- ent of metalaxyl in seed treatments (Dorrance 2014; Anon 2015). Therefore, fungicides tested for soybean seed treatments were labeled for foliar application and were not labeled to control Pythium damping-off. Aproach has not been labeled either foliar or seed treatments against Pythium damping-off, Rhizoctonia root rot and sudden death syndrome. In this study, the product has reduced the incidence of Pythium damping-off by 0.14% and showed 0.31 mt/ha yield ad- vantage compared with the untreated control (Table 3). According to Arysta LifeSciences, Evito foliar spray

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HEvAS: Headline Evaluation and Analysis System

HEvAS: Headline Evaluation and Analysis System

Automatic headline generation is a sub- task of one-line summarization with many reported applications. Evaluation of sys- tems generating headlines is a very chal- lenging and undeveloped area. We intro- duce the Headline Evaluation and Anal- ysis System (HEvAS) that performs au- tomatic evaluation of systems in terms of a quality of the generated headlines. HEvAS provides two types of metrics– one which measures the informativeness of a headline, and another that measures its readability. The results of evaluation can be compared to the results of base- line methods which are implemented in HEvAS. The system also performs the sta- tistical analysis of the evaluation results and provides different visualization charts. This paper describes all evaluation met- rics, baselines, analysis, and architecture, utilized by our system.

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Impact of financial news headline and content to market sentiment

Impact of financial news headline and content to market sentiment

In this research, the dataset were collected from the local online newspapers which are The Star Online, The National News Agency of Malaysia (BERNAMA), The Sun Daily, and The New Straits Times (NST). However, we only collected the financial and business related news articles. These news articles contain news related to individual stock in Kuala Lumpur Stock Exchange (KLSE) or also known as Bursa Malaysia. The topics include, but not limited to earning announcements, quarterly reports, annual reports, and product unveilings. These articles were collected in the first half of 2013. Each news article contains two elements which are the news headline and the content of the news. Approximately 200 financial news articles were collected and used in the experiments.

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A Large Scale Multi Length Headline Corpus for Analyzing Length Constrained Headline Generation Model Evaluation

A Large Scale Multi Length Headline Corpus for Analyzing Length Constrained Headline Generation Model Evaluation

Rush et al. (2015) created the first approach to neural abstractive summarization. They generated a headline from the first sentence of a news ar- ticle in the AEG (Napoles et al., 2012), which contains an enormous number of pairs of head- lines and articles. After their study, a num- ber of researchers addressed this task: For ex- ample, Chopra et al. (2016) used the encoder- decoder framework (Sutskever et al., 2014; Bah- danau et al., 2015) and Nallapati et al. (2016) in- corporated additional features into the model, such as parts-of-speech tags and named entities. Suzuki and Nagata (2017) proposed word-frequency esti- mation to reduce the repeated phrases being gener- ated. Zhou et al. (2017) proposed a gating mecha- nism (sGate) to ensure that important information is selected at each decoding step.

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