Online traces of human activity offer novel opportunities to study the dynamics of complex knowledge exchange networks, in particular how emergent patterns of collective attention determine what new information is generated and consumed. Can we measure the relationship between demand and supply for new information about a topic? We propose a normalization method to compare attention bursts statistics across topics with heterogeneous distribution of attention. Through analysis of a massive dataset on traffic to Wikipedia, we find that the production of new knowledge is associated to significant shifts of collective attention, which we take as proxy for its demand. This is consistent with a scenario in which allocation of attention toward a topic stimulates the demand for information about it, and in turn the supply of further novel information.

However, attention spikes only for a limited time span, during which new content has higher chances of receiving traffic, compared to content created later or earlier on. Our attempt to quantify demand and supply of information, and our finding about their temporal ordering, may lead to the development of the fundamental laws of the attention economy, and to a better understanding of social exchange of knowledge information networks. Massive logs on online human activity create new possibilities to study complex socio-economic phenomena. Among these, the dynamics of knowledge exchange networks, and in particular the emergent interactions between producers and consumers of information, have not been explored like the flows of material goods.

ABA fought a bitter war with the established National Basketball. Association (the NBA) for players, fans, and media attention. • The ABA was the league that played with. Effects of Merger. • The merger was legal: ABA was entering bankruptcy. • Anti-competitive: NBA gained full control of the market. • Monopoly with huge.

Yet they have a critical impact on our opinions, decisions, and lives. An overwhelming amount of information stimuli compete for our cognitive resources, giving rise to the economy of attention, first theorized by Simon. At the aggregate level, this phenomenon is often referred to as collective attention. Work on collective attention has mainly focused on the consumption of information. Characteristic signatures of information consumption have been shown to correlate with real-world events, such as the spread of influenza, financial stock returns, scientific performance, and box office results. The production side of the equation — whether and how the creation of information is driven by demand — has been explored to a limited extent in the literature, owing in part to the challenges in quantifying information demand.

Imitation of popular content, for instance, is the simplest form of supply matching demand for information. However, while examples of imitation of online contents abound, they do not point to a quantitative relationship between the demand for and production of information. In looking at the role of attention as a possible driver for the generation of novel content, Huberman et al. Found a positive correlation between the productivity of YouTube contributors and the number of views of their previous videos. This confirms that prestige is a powerful motivation for creation of knowledge. Here we tackle the measurement of demand and supply of information goods and their relative ordering in time. Looking at attention toward a specific piece of information, no link between traffic bursts and the number of edits to a Wikipedia article has been found so far.

We focus on the creation of Wikipedia articles as a better proxy for the production of information, and on visits to topically related articles as a proxy for its demand. Analysis of Wikipedia traffic data thus allows us to study how the generation of new knowledge about a topic precedes or follows its demand. More specifically, we are interested in how attention toward topics changes around the time that new knowledge about them is created.

Moreover, we want to do so by comparing a broad range of topics. Sudden changes of attention, or “bursts”, have been traditionally studied using the logarithmic derivative Δ N t/ N t, where N t is the number of visits or links accrued by a topic (e.g. A Wikipedia page, a YouTube video, etc.) during a fixed sampling interval t and the numerator is customarily defined as Δ N t = N t +1 − N t. However, the distribution of Δ N/ N is known to be broad, with a heavy-tail decay that follows a power-law distribution. This lack of a characteristic scale thus makes it difficult to use Δ N/ N for comparing diverse topics. Here we propose to use a different measure of traffic change based on a simple normalization of the traffic, in a way that takes into account this and other confounding factors, such as traffic seasonality and circadian rhythms of activity. Wikipedia is currently the fifth most visited Internet website, and includes 30 million articles in 287 languages.

The English version alone consists of roughly 4.4 million articles and is consulted, on average, by about 300 million people every day. Each entry, or article, of Wikipedia corresponds to a separate web page. Wikipedia can thus be regarded as a large information network, where one can identify broad macroscopic topics. By way of example, depicts the traffic to two high-profile articles and to their neighbors. The two articles are selected from the 2012 Google Zeitgeist. We define a topic as such a page, together with all of its neighbors — articles linked by it or linking to it, subsequently to its creation (see Methods).

The networks formed by the two topics are shown in. (a), Time series of traffic. The grey lines represent the daily traffic to articles that are linked from/to the article “2012 Summer Olympics,” according to a recent snapshot of Wikipedia (see Methods). For visualization purposes, only a random sample of 100 neighbors is shown. The focal page is represented by the black solid line; red and gold lines represent the average and median traffic, respectively. The vertical black segments represent the times when new linked articles are created (see Methods).

(b), Network of neighbors of “2012 Summer Olympics.” White nodes represent the neighbor articles predating 2012; colored nodes correspond to neighbors created in 2012. The size of the nodes is proportional to their yearly traffic volume; their position was computed using the ARF layout. (c and d), Same visualizations as (a) and (b) for the entry about Hurricane Sandy and its neighbors. New articles tend to be peripheral to these networks. The volume of traffic to a page or a topic is measured by daily browser requests for the corresponding pages. Weekly fluctuations are evident in the traffic patterns shown in. It is also possible to observe synchronous bursts of activity, corresponding to increased attention toward the topic.

For the Olympics topic, such increase of attention takes the form of an anticipatory buildup, leading to two peaks around the opening and closing ceremonies, followed by a relaxation at a lower baseline. For Hurricane Sandy a sudden spike occurs at the time of creation of the main article, due to the demand of information about the effects of the hurricane. Phenomena like these have been already observed in a wide range of information-rich environments,. During the period of increased attention we see a previously unobserved phenomenon, namely that new articles about the Olympic Games are created at a higher frequency. A weaker pattern is observed for Hurricane Sandy too. To quantify the temporal relation between demand and production of information about a topic, we performed a systematic study over a large sample of articles.

An increase of attention toward the topic of an article is revealed by an increase in requests for pages in that topic compared to other topics. Let us consider a newly created article.

A burst of attention for pages related to it occurring before its creation is consistent with a model in which demand drives the supply of information. Conversely, a burst that follows its creation suggests that demand follows supply. On the other hand, if traffic bursts concomitant with the creation of new articles are no different than those observed at any other time, then we shall conclude that production and consumption of information are two unrelated processes. As the focus of public attention is constantly shifting, we also explore how long is the timespan during which demand and supply for new information are effectively associated to each other. In other words, is there an ideal period during which newly created information will have better chances of receiving more traffic relative to its baseline? We address this question by measuring the time lag between the most recent peak of traffic toward the pages in the topic of a new article and its time of creation. We relate this lag to the traffic received by the new article.

Statistics of attention bursts Our analysis is focused on the year 2012. We collected the neighbors of 93,491 pages created during that year. For each created page we considered the two weeks before and after its creation, and measured the volume of traffic to its topic in each week. We characterize the typical traffic to the topic in the week after and before with the median traffic to neighbors V ( a) and V ( b), respectively.

Let us define infra-week traffic volume change Δ V = V ( a) − V ( b), total volume V = V ( a) + V ( b), and relative volume change Δ V/ V. For comparison purposes, we collected the neighbors of a roughly equally-sized sample of pre-existing articles (created before 2012) and analogously computed their relative infra-week changes in traffic volume over random two-week windows in 2012.

Articles in the baseline sample are older and therefore tend to have more neighbors, as shown in. This and other temporal effects are discounted by considering the relative change in volume Δ V/ V (see Methods). (a), Cumulative distribution of neighborhood size for articles created in 2012 (solid), and pre-existing 2012 (dashed).

Neighbors are all articles linking to or from the focal page. Older articles tend to have larger neighborhoods. (b), Absolute infra-week traffic change Δ V as a function of total traffic volume V for articles created in 2012. Even though some topics may receive hundreds of million visits, the change in traffic volume is on average much smaller. Pre-existing pages show a very similar pattern. Boxes stretch from the first to the third quartile, and whiskers represent the 99% confidence interval. Gray segments within boxes indicate the median.

The dashed line is a guide to the eye for linear scaling. (c), Distribution of the relative change in traffic volume for 2012 (solid) and pre-existing (dashed) pages. (d), Log odds ratio comparing pages created in 2012 versus existing pages as a function of relative traffic change, for the whole sample (circles), and for a sub-sample of 16,816 pages (18%) with V >2 × 10 5 visits (triangles). The dashed gray line indicates equal odds. We observe that the volume change Δ V scales sublinearly with the total volume V, as illustrated in. Consequently Δ V / V goes to zero as V increases.

While the distributions of Δ V/ V are sharply peaked around zero in both samples (), they are different: a non-parametric Kolmogorov-Smirnov test rejects the null hypothesis that the two samples of relative traffic change are drawn from the same distribution ( D = 0.034, p 0) the generation of new knowledge, comparison with the baseline yields a significant shift toward the former case, suggesting that consumption anticipates the production of information more often than the converse. Top attention bursts Which kinds of articles precede or follow demand for information? In we list a few articles with the largest positive and negative bursts. Topics that precede demand (Δ V/ V >0) tend to be about current and possibly unexpected events, such as a military operation in the Middle East and the killing of the U.S.

Ambassador in Libya. These articles are created almost instantaneously with the event, to meet the subsequent demand.

Articles that follow demand (Δ V/ V. Collective attention span We look at a random subset of 20,000 Wikipedia articles drawn from the previous sample of pages created during the course of 2012. For a generic page, let t c denote the day it was created. For such page we also define V c as the volume of traffic in its first week of existence. Analogously, let V p be the peak daily traffic volume to neighbors measured over an observation window of approximately 60 days centered at t c, and let t p be the day of the peak. To detect the peak of traffic to neighbors, we smooth the data with a moving average in a centered 7-day window. To quantify whether a certain amount of visits to a target article constitutes a burst of attention relative to the baseline attention to its topic, in we plot V c/ V p as a function of the lag in days δ = t p − t c, averaged across pages with the same value of δ.

Error bars represent two standard deviations around the mean. A lag of δ = 0 represents a peak of attention that occurs on the day of creation of the new article. Negative/positive values of δ indicate that the attention peak occurred before/ after the creation of the article.

As shown in the figure, new articles created a few days before or after the peak (−3 ≤ δ ≤ +3) tend to receive substantially higher traffic than those created at a later or earlier time. The maximum is achieved when an article is created two or three days after the peak. Supply and demand of information Our result shows that in many cases demand for information precedes its supply. We propose a model to interpret this finding, analogous to the law of supply and demand.

An increase in demand indicates a willingness to pay a higher price for a physical good, which in turn leads to an increase in supply. In the domain of information, attention plays the role of price: an increase in demand for information about a topic indicates a higher attention toward that topic, which in turns leads to the generation of additional information about it. This model predicts a causal link between demand and supply of information. Our empirical observations are consistent with this prediction, and may represent a first step toward the development of the fundamental laws of the attention economy. Whether there is a hard causal link between demand and supply remains an open question. Indeed, other sources of attention, such as conversations on social media, may generate traffic to existing pages as well as trigger the creation of new pages.

Our main contribution here has been to establish a quantitative relation between the timing of demand and supply of information. A definition of “information” is more elusive than that of material goods; and quantifying demand is particularly hard in this case. Another caveat is that not all requests are generated as a result of demand for information.

A number of requests to related articles are likely to be generated by the very creators of new entries; one could hardly create new knowledge about some topic without consulting existing pages about it. This is a source of potential bias for our measure of demand especially in the case of low-traffic topics, such as entries about small towns or niche musical bands.

On the other hand, significant bursts in volume are observed for popular topics as well (cf. Such bursts could not possibly be generated by the activity of contributors, who are a small percentage of the Wikipedia audience.

Collective attention span In addition to uncovering for the first time a previously unobserved link between collective attention and production of new information, we also find that new articles created shortly before or after the peak of traffic to their related pages tend to garner more views than those created too early or too late. Collective attention concentrates only for a brief period of time — a span of about ±3 days — on these new articles. Other signals about content creation In this study we restricted our notion of content production to the creation of new articles.

Wikipedia lets any contributor add further information after the initial publication of an article, but our method does not capture these instances of content creation. As mentioned before, the sequence of revisions to an article is not a good proxy for content production namely because of its noisy nature. To find a signal in it, one would need to identify only “major” updates.

Unfortunately, this is hard to do on the basis of text change alone, as the distribution of edit size is heavy-tailed. Furthermore the idiosyncrasies of the editorial process on Wikipedia further complicate things: for example, if a long chunk of text is moved to another article, one would see a large change in terms of text removed and added, even though no novel information has been produced. Devising more sophisticated notions of content creation in this context would be highly desirable in the future. Future work As a practical consequence of our finding, volumetric data about collective attention, such as searches, reviews, and ratings, which now abound online, may be used as indicators of what kinds of new ideas and innovations will ensue.

Our analysis focuses on aggregate-level behaviors. Models of individual browsing behavior could shed more light on how people allocate their attention among competing information stimuli online. Given the sensitive nature of the personal information revealed by individual browsing habits, validating such models with data is a challenge, as revealed by the recent discussions about the trade-offs between data-driven social science research and individual privacy rights.

Nevertheless, further empirical analyses and theoretical models of individual and collective dynamics of attention will lead a better understanding of the social exchange of knowledge in online and offline information networks. Data collection In our analysis we used the public dataset generated by the servers of the Wikimedia Foundation.

Traffic volume is the number of non-unique HTTP requests that an article receives, as a proxy for the popularity of the subject. We collected data about hourly traffic to the neighbors of Wikipedia articles created during 2012. The data were pre-processed for analysis. We conflated titles that automatically redirect to other entries.

We used the information in the ‘redirect’ table to perform this check. We considered only pages created by humans, using a recent list of all known bots to discard automatically-generated pages.

Neighbors were found by looking at the ‘pagelinks’ table, after resolving redirects. Page creation To check whether a page was actually created during 2012 we consulted the time stamp of its earliest recorded revision (the reference time stamp). Unfortunately, this information is not always accurate since Wikipedia pages can be merged, migrated, have their edit history fully or partially deleted, or even lost. We thus checked that no traffic to the page had been recorded in our dataset in a 50-week exclusion window before the reference time stamp.

However, because it is customary to include links to missing entries in order to encourage other contributors to create them, we found this criterion to produce too many false negatives. We settled for a small threshold, allowing pages with at most 5% (420) non-null hourly observations in the exclusion window. Links At its earliest stage a Wikipedia article rarely contains more than a handful of sentences and links. As a consequence, looking at the early set of neighbors would yield very sparse information. On the other hand, deletion of links is rare. Therefore we collected the neighbors that link to and are linked by the page at the present day.

Relative traffic change Let us consider a focal page with N neighbours and an observation window of length L centered around a reference time t c, which is the time when the page is created. The total traffic volume each neighbor receives before and after t c corresponds to random variables and, respectively. The average volume change indicates whether, on average, attention to a neighbor is more concentrated before the creation of the page ( ) or after ( ). Even though it accounts for the broad distribution of neighborhood sizes (see ), does not guarantee a fair comparison between topics for two reasons: first, the distribution of attention across topics is broad (as shown in ); second, Web traffic is known to follow circadian, weekly, and seasonal rhythms. Over a week, an overall change in traffic volume visits may represent a dramatic surge of attention if observed over a group of pages that average 100 visits per week. However, it would be barely noticeable if the same pages averaged 10 4 visits per week.

To overcome these problems, let us define the relative (median) traffic change: where V () is the median traffic over a neighbor. We choose to use the median since it is a more robust estimator in the presence of outliers, and almost every article in our samples has at least one very high-traffic neighbor (e.g., “United States”), whose volume of traffic is insensitive to all but the most high-profile events recorded in the dataset. The Bet Wattpad Pdf Free here. We also repeated our analysis using the sample mean and found qualitatively similar results. The length L of the observation window must be chosen considering a trade-off between competing requirements.

Most attention spikes tend to be relatively brief — on the scale of the day — and so the value of L should not be too large, to avoid lumping together consecutive attention bursts. On the other hand, because of the strong circadian and weekly cycles that we see in, L cannot be too small, otherwise these fluctuations would dominate the signal for all but the largest bursts. We therefore consider a two-week observation window ( L = 14 days), centered at the time of creation of the new page. Baseline sample To collect the baseline data we drew at random without replacement an existing page (i.e., created before 2012) for each new page, and extracted traffic to its neighbors at a random time stamp during 2012. We also repeated the analysis with a different baseline sample, where instead of a random time stamp we used the time of creation of the associated new page, and found similar results.

Edition used: Alfred Marshall, Principles of Economics (London: Macmillan and Co. Available in the following formats: 45.2 MB This is a facsimile or image-based PDF made from scans of the original book. 1.38 KB MAchine-Readable Cataloging record. 1.97 MB This is an E-book formatted for Amazon Kindle devices. 3.13 MB This text-based PDF or EBook was created from the HTML version of this book and is part of the Portable Library of Liberty. Chemistry Programs For Ti Nspire Cx Cas Handheld. 2.2 MB This version has been converted from the original text. Every effort has been taken to translate the unique features of the printed book into the HTML medium.

2.2 MB This is a simplifed HTML format, intended for screen readers and other limited-function browsers. 1.25 MB ePub standard file for your iPad or any e-reader compatible with that format About this Title: This is the 8th edition of what is regarded to be the first “modern” economics textbook, leading in various editions from the 19th into the 20th century. The final 8th edition was Marshall’s most-used and most-cited. Copyright information: The text is in the public domain. Fair use statement: This material is put online to further the educational goals of Liberty Fund, Inc. Unless otherwise stated in the Copyright Information section above, this material may be used freely for educational and academic purposes.

It may not be used in any way for profit. Table of Contents: • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • •. CONTENTS • BOOK I • PRELIMINARY SURVEY.

• BOOK I, CHAPTER I INTRODUCTION. • BOOK I, CHAPTER II THE SUBSTANCE OF ECONOMICS.

• BOOK I, CHAPTER III ECONOMIC GENERALIZATIONS OR LAWS. • BOOK I, CHAPTER IV THE ORDER AND AIMS OF ECONOMIC STUDIES. • BOOK II • SOME FUNDAMENTAL NOTIONS. • BOOK II, CHAPTER I INTRODUCTORY. • BOOK II, CHAPTER II WEALTH. • BOOK II, CHAPTER III PRODUCTION.

• BOOK II, CHAPTER IV INCOME. • BOOK III • ON WANTS AND THEIR SATISFACTION. • BOOK III, CHAPTER I INTRODUCTORY. • BOOK III, CHAPTER II WANTS IN RELATION TO ACTIVITIES.

• BOOK III, CHAPTER III GRADATIONS OF CONSUMERS' DEMAND. • BOOK III, CHAPTER IV THE ELASTICITY OF WANTS.

• Note on Statistics of Consumption. • BOOK III, CHAPTER V CHOICE BETWEEN DIFFERENT USES OF THE SAME THING. IMMEDIATE AND DEFERRED USES. • BOOK III, CHAPTER VI VALUE AND UTILITY. • BOOK IV • THE AGENTS OF PRODUCTION. Land, Labour, Capital and Organization. • BOOK IV, CHAPTER I INTRODUCTORY.

• BOOK IV, CHAPTER II THE FERTILITY OF LAND. • BOOK IV, CHAPTER III THE FERTILITY OF LAND, CONTINUED. THE TENDENCY TO DIMINISHING RETURN. • Note on the Law of Diminishing Return. • BOOK IV, CHAPTER IV THE GROWTH OF POPULATION. • BOOK IV, CHAPTER V THE HEALTH AND STRENGTH OF THE POPULATION.

• BOOK IV, CHAPTER VI INDUSTRIAL TRAINING. • BOOK IV, CHAPTER VII THE GROWTH OF WEALTH.

• Note on the Statistics of the Growth of Wealth. • BOOK IV, CHAPTER VIII INDUSTRIAL ORGANIZATION. • BOOK IV, CHAPTER IX INDUSTRIAL ORGANIZATION, CONTINUED. DIVISION OF LABOUR. THE INFLUENCE OF MACHINERY. • BOOK IV, CHAPTER X INDUSTRIAL ORGANIZATION, CONTINUED.

THE CONCENTRATION OF SPECIALIZED INDUSTRIES IN PARTICULAR LOCALITIES. • BOOK IV, CHAPTER XI INDUSTRIAL ORGANIZATION, CONTINUED. PRODUCTION ON A LARGE SCALE. • BOOK IV, CHAPTER XII INDUSTRIAL ORGANIZATION, CONTINUED.

BUSINESS MANAGEMENT. • BOOK IV, CHAPTER XIII CONCLUSION. CORRELATION OF THE TENDENCIES TO INCREASING AND TO DIMINISHING RETURN. • BOOK V • GENERAL RELATIONS OF DEMAND, SUPPLY AND VALUE. • BOOK V, CHAPTER I INTRODUCTORY. • BOOK V, CHAPTER II TEMPORARY EQUILIBRIUM OF DEMAND AND SUPPLY.

• BOOK V, CHAPTER III EQUILIBRIUM OF NORMAL DEMAND AND SUPPLY. • BOOK V, CHAPTER IV THE INVESTMENT AND DISTRIBUTION OF RESOURCES.

• BOOK V, CHAPTER V EQUILIBRIUM OF NORMAL DEMAND AND SUPPLY, CONTINUED, WITH REFERENCE TO LONG AND SHORT PERIODS. • BOOK V, CHAPTER VI JOINT AND COMPOSITE DEMAND. JOINT AND COMPOSITE SUPPLY. • BOOK V, CHAPTER VII PRIME AND TOTAL COST IN RELATION TO JOINT PRODUCTS.

COST OF MARKETING. INSURANCE AGAINST RISK. COST OF REPRODUCTION. • BOOK V, CHAPTER VIII MARGINAL COSTS IN RELATION TO VALUES.

GENERAL PRINCIPLES. • BOOK V, CHAPTER IX MARGINAL COSTS IN RELATION TO VALUES. GENERAL PRINCIPLES, CONTINUED. • BOOK V, CHAPTER X MARGINAL COSTS IN RELATION TO AGRICULTURAL VALUES.

• BOOK V, CHAPTER XI MARGINAL COSTS IN RELATION TO URBAN VALUES. • BOOK V, CHAPTER XII EQUILIBRIUM OF NORMAL DEMAND AND SUPPLY, CONTINUED, WITH REFERENCE TO THE LAW OF INCREASING RETURN. • BOOK V, CHAPTER XIII THEORY OF CHANGES OF NORMAL DEMAND AND SUPPLY IN RELATION TO THE DOCTRINE OF MAXIMUM SATISFACTION.

• BOOK V, CHAPTER XIV THE THEORY OF MONOPOLIES. • BOOK V, CHAPTER XV SUMMARY OF THE GENERAL THEORY OF EQUILIBRIUM OF DEMAND AND SUPPLY. • BOOK VI • THE DISTRIBUTION OF THE NATIONAL INCOME. • BOOK VI, CHAPTER I PRELIMINARY SURVEY OF DISTRIBUTION. • BOOK VI, CHAPTER II PRELIMINARY SURVEY OF DISTRIBUTION, CONTINUED. • BOOK VI, CHAPTER III EARNINGS OF LABOUR.

• BOOK VI, CHAPTER IV EARNINGS OF LABOUR, CONTINUED. • BOOK VI, CHAPTER V EARNINGS OF LABOUR, CONTINUED. • BOOK VI, CHAPTER VI INTEREST OF CAPITAL. • BOOK VI, CHAPTER VII PROFITS OF CAPITAL AND BUSINESS POWER. • BOOK VI, CHAPTER VIII PROFITS OF CAPITAL AND BUSINESS POWER, CONTINUED.

• BOOK VI, CHAPTER IX RENT OF LAND. • BOOK VI, CHAPTER X LAND TENURE.

• BOOK VI, CHAPTER XI GENERAL VIEW OF DISTRIBUTION. • BOOK VI, CHAPTER XII GENERAL INFLUENCES OF ECONOMIC PROGRESS. • BOOK VI, CHAPTER XIII PROGRESS IN RELATION TO STANDARDS OF LIFE. • APPENDIX A THE GROWTH OF FREE INDUSTRY AND ENTERPRISE.

• APPENDIX B THE GROWTH OF ECONOMIC SCIENCE. • APPENDIX C THE SCOPE AND METHOD OF ECONOMICS. • APPENDIX D USES OF ABSTRACT REASONING IN ECONOMICS. • APPENDIX E DEFINITIONS OF CAPITAL.

• APPENDIX F BARTER. • APPENDIX G THE INCIDENCE OF LOCAL RATES, WITH SOME SUGGESTIONS AS TO POLICY. • APPENDIX H LIMITATIONS OF THE USE OF STATICAL ASSUMPTIONS IN REGARD TO INCREASING RETURN. • APPENDIX I RICARDO'S THEORY OF VALUE. • APPENDIX J THE DOCTRINE OF THE WAGES-FUND. • APPENDIX K CERTAIN KINDS OF SURPLUS.

• APPENDIX L RICARDO'S DOCTRINE AS TO TAXES AND IMPROVEMENTS IN AGRICULTURE. BOOK I, CHAPTER III: ECONOMIC GENERALIZATIONS OR LAWS. It is the business of economics, as of almost every other science, to collect facts, to arrange and interpret them, and to draw inferences from them. 'Observation and description, definition and classification are the preparatory activities.

But what we desire to reach thereby is a knowledge of the interdependence of economic phenomena. Induction and deduction are both needed for scientific thought as the right and left foot are both needed for walking.' The methods required for this twofold work are not peculiar to economics; they are the common property of all sciences. All the devices for the discovery of the relations between cause and effect, which are described in treatises on scientific method, have to be used in their turn by the economist: there is not any one method of investigation which can properly be called the method of economics; but every method must be made serviceable in its proper place, either singly or in combination with others. And as the number of combinations that can be made on the chess-board, is so great that probably no two games exactly alike were ever played; so no two games which the student plays with nature to wrest from her her hidden truths, which were worth playing at all, ever made use of quite the same methods in quite the same way. But in some branches of economic inquiry and for some purposes, it is more urgent to ascertain new facts, than to trouble ourselves with the mutual relations and explanations of those which we already have.

While in other branches there is still so much uncertainty as to whether those causes of any event which lie on the surface and suggest themselves at first are both true causes of it and the only causes of it, that it is even more urgently needed to scrutinize our reasoning about facts which we already know, than to seek for more facts. For this and other reasons, there always has been and there probably always will be a need for the existence side by side of workers with different aptitudes and different aims, some of whom give their chief attention to the ascertainment of facts, while others give their chief attention to scientific analysis; that is taking to pieces complex facts, and studying the relations of the several parts to one another and to cognate facts. It is to be hoped that these two schools will always exist; each doing its own work thoroughly, and each making use of the work of the other. Thus best may we obtain sound generalizations as to the past and trustworthy guidance from it for the future. Those physical sciences, which have progressed most beyond the points to which they were brought by the brilliant genius of the Greeks, are not all of them strictly speaking 'exact sciences.'

But they all aim at exactness. That is they all aim at precipitating the result of a multitude of observations into provisional statements, which are sufficiently definite to be brought under test by other observations of nature. These statements, when first put forth, seldom claim a high authority.

But after they have been tested by many independent observations, and especially after they have been applied successfully in the prediction of coming events, or of the results of new experiments, they graduate as laws. A science progresses by increasing the number and exactness of its laws; by submitting them to tests of ever increasing severity; and by enlarging their scope till a single broad law contains and supersedes a number of narrower laws, which have been shown to be special instances of it. In so far as this is done by any science, a student of it can in certain cases say with authority greater than his own (greater perhaps than that of any thinker, however able, who relies on his own resources and neglects the results obtained by previous workers), what results are to be expected from certain conditions, or what are the true causes of a certain known event. Although the subject-matter of some progressive physical sciences is not, at present at least, capable of perfectly exact measurement; yet their progress depends on the multitudinous co-operation of armies of workers. They measure their facts and define their statements as closely as they can: so that each investigator may start as nearly as possible where those before him left off.

Economics aspires to a place in this group of sciences: because though its measurements are seldom exact, and are never final; yet it is ever working to make them more exact, and thus to enlarge the range of matters on which the individual student may speak with the authority of his science. Let us then consider more closely the nature of economic laws, and their limitations. Every cause has a tendency to produce some definite result if nothing occurs to hinder it. Thus gravitation tends to make things fall to the ground: but when a balloon is full of gas lighter than air, the pressure of the air will make it rise in spite of the tendency of gravitation to make it fall. The law of gravitation states how any two things attract one another; how they tend to move towards one another, and will move towards one another if nothing interferes to prevent them.

The law of gravitation is therefore a statement of tendencies. It is a very exact statement—so exact that mathematicians can calculate a Nautical Almanac, which will show the moments at which each satellite of Jupiter will hide itself behind Jupiter. They make this calculation for many years beforehand; and navigators take it to sea, and use it in finding out where they are. Now there are no economic tendencies which act as steadily and can be measured as exactly as gravitation can: and consequently there are no laws of economics which can be compared for precision with the law of gravitation. But let us look at a science less exact than astronomy.

The science of the tides explains how the tide rises and falls twice a day under the action of the sun and the moon: how there are strong tides at new and full moon, and weak tides at the moon's first and third quarter; and how the tide running up into a closed channel, like that of the Severn, will be very high; and so on. Thus, having studied the lie of the land and the water all round the British isles, people can calculate beforehand when the tide will probably be at its highest on any day at London Bridge or at Gloucester; and how high it will be there. They have to use the word probably, which the astronomers do not need to use when talking about the eclipses of Jupiter's satellites.

For, though many forces act upon Jupiter and his satellites, each one of them acts in a definite manner which can be predicted beforehand: but no one knows enough about the weather to be able to say beforehand how it will act. A heavy downpour of rain in the upper Thames valley, or a strong north-east wind in the German Ocean, may make the tides at London Bridge differ a good deal from what had been expected. The laws of economics are to be compared with the laws of the tides, rather than with the simple and exact law of gravitation. For the actions of men are so various and uncertain, that the best statement of tendencies, which we can make in a science of human conduct, must needs be inexact and faulty. This might be urged as a reason against making any statements at all on the subject; but that would be almost to abandon life. Life is human conduct, and the thoughts and emotions that grow up around it. By the fundamental impulses of our nature we all—high and low, learned and unlearned—are in our several degrees constantly striving to understand the courses of human action, and to shape them for our purposes, whether selfish or unselfish, whether noble or ignoble.

And since we must form to ourselves some notions of the tendencies of human action, our choice is between forming those notions carelessly and forming them carefully. The harder the task, the greater the need for steady patient inquiry; for turning to account the experience, that has been reaped by the more advanced physical sciences; and for framing as best we can well thought-out estimates, or provisional laws, of the tendencies of human action. The term 'law' means then nothing more than a general proposition or statement of tendencies, more or less certain, more or less definite. Many such statements are made in every science: but we do not, indeed we can not, give to all of them a formal character and name them as laws. We must select; and the selection is directed less by purely scientific considerations than by practical convenience. If there is any general statement which we want to bring to bear so often, that the trouble of quoting it at length, when needed, is greater than that of burdening the discussion with an additional formal statement and an additional technical name, then it receives a special name, otherwise not.

Thus a law of social science, or a Social Law, is a statement of social tendencies; that is, a statement that a certain course of action may be expected under certain conditions from the members of a social group. Economic laws, or statements of economic tendencies, are those social laws which relate to branches of conduct in which the strength of the motives chiefly concerned can be measured by a money price. There is thus no hard and sharp line of division between those social laws which are, and those which are not, to be regarded also as economic laws. For there is a continuous gradation from social laws concerned almost exclusively with motives that can be measured by price, to social laws in which such motives have little place; and which are therefore generally as much less precise and exact than economic laws, as those are than the laws of the more exact physical sciences. Corresponding to the substantive 'law' is the adjective 'legal.' But this term is used only in connection with 'law' in the sense of an ordinance of government; not in connection with 'law' the sense of a statement of relation between cause and effect.

The adjective used for this purpose is derived from 'norma,' a term which is nearly equivalent to 'law,' and might perhaps with advantage be substituted for it in scientific discussions. And following our definition of an economic law, we may say that the course of action which may be expected under certain conditions from the members of an industrial group is the normal action of the members of that group relatively to those conditions. This use of the term Normal has been misunderstood; and it may be well to say something as to the unity in difference which underlies various uses of the term. When we talk of a Good man or a Strong man, we refer to excellence or strength of those particular physical mental or moral qualities which are indicated in the context. A strong judge has seldom the same qualities as a strong rower; a good jockey is not always of exceptional virtue. In the same way every use of the term normal implies the predominance of certain tendencies which appear likely to be more or less steadfast and persistent in their action over those which are relatively exceptional and intermittent. Illness is an abnormal condition of man: but a long life passed without any illness is abnormal.

During the melting of the snows, the Rhine rises above its normal level: but in a cold dry spring when it is less than usual above that normal level, it may be said to be abnormally low (for that time of year). In all these cases normal results are those which may be expected as the outcome of those tendencies which the context suggests; or, in other words, which are in accordance with those 'statements of tendency,' those Laws or Norms, which are appropriate to the context. This is the point of view from which it is said that normal economic action is that which may be expected in the long run under certain conditions (provided those conditions are persistent) from the members of an industrial group. It is normal that bricklayers in most parts of England are willing to work for 10 d. An hour, but refuse to work for 7 d.

In Johannesburg it may be normal that a brick-layer should refuse work at much less than £1 a day. The normal price of bona fide fresh laid eggs may be taken to be a penny when nothing is said as to the time of the year: and yet threepence may be the normal price in town during January; and twopence may be an abnormally low price then, caused by 'unseasonable' warmth. Another misunderstanding to be guarded against arises from the notion that only those economic results are normal, which are due to the undisturbed action of free competition. But the term has often to be applied to conditions in which perfectly free competition does not exist, and can hardly even be supposed to exist; and even where free competition is most dominant, the normal conditions of every fact and tendency will include vital elements that are not a part of competition nor even akin to it. Thus, for instance, the normal arrangement of many transactions in retail and wholesale trade, and on Stock and Cotton Exchanges, rests on the assumption that verbal contracts, made without witnesses, will be honourably discharged; and in countries in which this assumption cannot legitimately be made, some parts of the Western doctrine of normal value are inapplicable. Again, the prices of various Stock Exchange securities are affected 'normally' by the patriotic feelings not only of the ordinary purchasers, but of the brokers themselves: and so on. Lastly it is sometimes erroneously supposed that normal action in economics is that which is right morally.

But that is to be understood only when the context implies that the action is being judged from the ethical point of view. When we are considering the facts of the world, as they are, and not as they ought to be, we shall have to regard as 'normal' to the circumstances in view, much action which we should use our utmost efforts to stop. For instance, the normal condition of many of the very poorest inhabitants of a large town is to be devoid of enterprise, and unwilling to avail themselves of the opportunities that may offer for a healthier and less squalid life elsewhere; they have not the strength, physical, mental and moral, required for working their way out of their miserable surroundings. The existence of a considerable supply of labour ready to make match-boxes at a very low rate is normal in the same way that a contortion of the limbs is a normal result of taking strychnine. It is one result, a deplorable result, of those tendencies the laws of which we have to study.

This illustrates one peculiarity which economics shares with a few other sciences, the nature of the material of which can be modified by human effort. Science may suggest a moral or practical precept to modify that nature and thus modify the action of laws of nature. For instance, economics may suggest practical means of substituting capable workers for those who can only do such work as match-box making; as physiology may suggest measures for so modifying the breeds of cattle that they mature early, and carry much flesh on light frames.

The laws of the fluctuation of credit and prices have been much altered by increased powers of prediction. Again when 'normal' prices are contrasted with temporary or market prices, the term refers to the dominance in the long run of certain tendencies under given conditions. But this raises some difficult questions which may be postponed. It is sometimes said that the laws of economics are 'hypothetical.'